onlinelibrary.wiley.com Open in urlscan Pro
2606:4700:7::a29f:8157  Public Scan

Submitted URL: https://bit.ly/3baff5w
Effective URL: https://onlinelibrary.wiley.com/doi/full/10.1002/jip.1482
Submission: On September 18 via manual from EC — Scanned from DE

Form analysis 8 forms found in the DOM

Name: thisJournalQuickSearchGET /action/doSearch

<form action="/action/doSearch" name="thisJournalQuickSearch" method="get" title="Quick Search">
  <div class="input-group option-0"><label for="searchField0" class="hiddenLabel">Search term</label><input type="search" name="AllField" id="searchField0" placeholder="Search" onfocus="this.value = this.value;" data-auto-complete-max-words="7"
      data-auto-complete-max-chars="32" data-contributors-conf="3" data-topics-conf="3" data-publication-titles-conf="3" data-history-items-conf="3" value="" tabindex="9" class="autocomplete actualQSInput quickSearchFilter ui-autocomplete-input"
      autocomplete="off"><span role="status" aria-live="polite" class="ui-helper-hidden-accessible"></span><input type="hidden" name="SeriesKey" value="15444767">
    <div class="search-options-wrapper quickSearchFilter">
      <a href="https://onlinelibrary.wiley.com/search/advanced?publication=15444767" title="" tabindex="12" class="advanced">  Advanced Search</a><a href="https://onlinelibrary.wiley.com/search/advanced?publication=15444767#citation" title="" tabindex="12" class="citation">  Citation Search</a>
    </div>
  </div><button type="submit" title="Search" tabindex="11" aria-label="Submit Search" class="btn quick-search__button icon-search"></button>
</form>

Name: defaultQuickSearchGET https://onlinelibrary.wiley.com/action/doSearch

<form action="https://onlinelibrary.wiley.com/action/doSearch" name="defaultQuickSearch" method="get" title="Quick Search">
  <div class="input-group option-1"><label for="searchField1" class="hiddenLabel">Search term</label><input type="search" name="AllField" id="searchField1" placeholder="Search" onfocus="this.value = this.value;" data-auto-complete-max-words="7"
      data-auto-complete-max-chars="32" data-contributors-conf="3" data-topics-conf="3" data-publication-titles-conf="3" data-history-items-conf="3" value="" tabindex="9" class="autocomplete actualQSInput quickSearchFilter ui-autocomplete-input"
      autocomplete="off"><span role="status" aria-live="polite" class="ui-helper-hidden-accessible"></span>
    <div class="search-options-wrapper quickSearchFilter">
      <a href="https://onlinelibrary.wiley.com/search/advanced" title="" tabindex="12" class="advanced">  Advanced Search</a><a href="https://onlinelibrary.wiley.com/search/advanced#citation" title="" tabindex="12" class="citation">  Citation Search</a>
    </div>
  </div><button type="submit" title="Search" tabindex="11" aria-label="Submit Search" class="btn quick-search__button icon-search"></button>
</form>

POST

<form method="post">
  <fieldset>
    <legend>Please review our <a href="https://onlinelibrary.wiley.com/termsAndConditions" target="_blank">Terms and Conditions of Use</a> and check box below to share full-text version of article.</legend>
    <div class="input-group"><label for="terms-and-conditions" class="checkbox--primary"><input id="terms-and-conditions" type="checkbox" value="yes" required="" name="terms-and-conditions"
          data-ajax-link="/action/generateShareUrl?doi=10.1002/jip.1482&amp;shareType=P2P&amp;format=PDF" data-shareable-link=""><span class="label-txt">I have read and accept the Wiley Online Library Terms and Conditions of Use</span></label></div>
  </fieldset>
  <hr class="separator">
  <div class="shareable"><label>Shareable Link</label>
    <p>Use the link below to share a full-text version of this article with your friends and colleagues. <a href="https://onlinelibrary.wiley.com/researchers/tools-resources/sharing" target="_blank" class="emphasis">Learn more.</a></p>
    <div class="shareable__box">
      <div class="shareable__text">
        <div class="shareable__field"><span id="shareable__text"></span><textarea tabindex="-1" class="shareable__text-area"></textarea></div>
      </div><button type="submit" disabled="" class="btn shareable__btn">Copy URL</button>
    </div>
    <div class="error shareable__error hidden"></div>
  </div>
</form>

POST /action/doLogin?societyURLCode=

<form action="/action/doLogin?societyURLCode=" class="bordered" method="post"><input type="hidden" name="id" value="67065c09-4a88-49cd-934c-ac707951d35c">
  <input type="hidden" name="popup" value="true">
  <input type="hidden" name="loginUri" value="/doi/full/10.1002/jip.1482">
  <input type="hidden" name="redirectUri" value="/doi/full/10.1002/jip.1482">
  <div class="input-group">
    <div class="label">
      <label for="username">Email or Customer ID</label>
    </div>
    <input id="username" class="login" type="text" name="login" value="" size="15" placeholder="Enter your email" autocorrect="off" spellcheck="false" autocapitalize="off" required="true">
    <div class="actions">
    </div>
  </div>
  <div class="input-group">
    <div class="label">
      <label for="password">Password</label>
    </div>
    <input id="password" class="password" type="password" name="password" value="" autocomplete="off" placeholder="Enter your password" autocorrect="off" spellcheck="false" autocapitalize="off" required="true">
    <span class="password-eye-icon icon-eye hidden"></span>
  </div>
  <div class="actions">
    <a href="/action/requestResetPassword" class="link show-request-reset-password">
                                Forgot password?
                            </a>
  </div>
  <div class="loginExtraBeans-dropZone" data-pb-dropzone="loginExtraBeans">
  </div>
  <div class="align-end">
    <span class="submit " disabled="disabled">
      <input class="button btn submit primary no-margin-bottom accessSubmit" type="submit" name="submitButton" value="Log In" disabled="disabled">
    </span>
  </div>
</form>

POST /action/changePassword

<form action="/action/changePassword" method="post">
  <div class="message error"></div>
  <input type="hidden" name="submit" value="submit">
  <div class="input-group">
    <div class="label">
      <label for="a589574e-bb98-4c6e-8fed-67365ff05357-old">Old Password</label>
    </div>
    <input id="a589574e-bb98-4c6e-8fed-67365ff05357-old" class="old" type="password" name="old" value="" autocomplete="off">
    <span class="password-eye-icon icon-eye hidden"></span>
  </div>
  <div class="input-group">
    <div class="label">
      <label for="a589574e-bb98-4c6e-8fed-67365ff05357-new">New Password</label>
    </div>
    <input id="a589574e-bb98-4c6e-8fed-67365ff05357-new" class="pass-hint new" type="password" name="new" value="" autocomplete="off">
    <span class="password-eye-icon icon-eye hidden"></span>
    <div class="password-strength-indicator" data-min="10" data-max="32" data-strength="4">
      <span class="text too-short">Too Short</span>
      <span class="text weak">Weak</span>
      <span class="text medium">Medium</span>
      <span class="text strong">Strong</span>
      <span class="text very-strong">Very Strong</span>
      <span class="text too-long">Too Long</span>
    </div>
  </div>
  <input class="button primary submit" type="submit" value="Submit" disabled="disabled">
</form>

POST /action/registration

<form action="/action/registration" class="registration-form" method="post"><input type="hidden" name="redirectUri" value="/doi/full/10.1002/jip.1482">
  <div class="input-group">
    <div class="label">
      <label for="4e647394-f751-4441-baa4-df426bca4b6e.email">Email</label>
    </div>
    <input id="4e647394-f751-4441-baa4-df426bca4b6e.email" class="email" type="text" name="email" value="" size="15">
  </div>
  <div class="submit">
    <input class="button submit primary" type="submit" value="Register" disabled="disabled">
  </div>
</form>

POST /action/requestResetPassword

<form action="/action/requestResetPassword" class="request-reset-password-form" method="post"><input type="hidden" name="requestResetPassword" value="true">
  <div class="input-group">
    <div class="input-group">
      <div class="label">
        <label for="email">Email</label>
      </div>
      <input id="email" class="email" type="text" name="email" value="" size="15" placeholder="Enter your email" autocorrect="off" spellcheck="false" autocapitalize="off">
    </div>
  </div>
  <div class="password-recaptcha-ajax"></div>
  <div class="message error"></div>
  <div class="form-btn">
    <input class="button btn primary submit" type="submit" name="submit" value="RESET PASSWORD" disabled="disabled">
  </div>
</form>

POST /action/requestUsername

<form action="/action/requestUsername" method="post"><input type="hidden" name="requestUsername" value="requestUsername">
  <div class="input-group">
    <div class="label">
      <label for="ac834f24-aa07-4ad2-9d13-f77c843f21cb.email">Email</label>
    </div>
    <input id="ac834f24-aa07-4ad2-9d13-f77c843f21cb.email" class="email" type="text" name="email" value="" size="15">
  </div>
  <div class="username-recaptcha-ajax">
  </div>
  <input class="button primary submit" type="submit" name="submit" value="Submit" disabled="disabled">
  <div class="center">
    <a href="#" class="cancel">Close</a>
  </div>
</form>

Text Content

 * Skip to Article Content
 * Skip to Article Information

Search withinThis JournalAnywhere
 * Search term
   Advanced Search Citation Search
 * Search term
   Advanced Search Citation Search

Login / Register
Journal of Investigative Psychology and Offender Profiling
Volume 15, Issue 1 p. 20-45
RESEARCH ARTICLE
Open Access



ON THE ANATOMY OF SOCIAL ENGINEERING ATTACKS—A LITERATURE-BASED DISSECTION OF
SUCCESSFUL ATTACKS


Jan-Willem Hendrik Bullée, 

Corresponding Author

Jan-Willem Hendrik Bullée

 * j.h.bullee@utwente.nl

Services, Cyber-security, and Safety Group (SCS), Faculty of EEMCS, University
of Twente, PO Box 217, Enschede, 7500 AE The Netherlands

Correspondence

Jan-Willem Bullée, Services, Cyber-security, and Safety Group (SCS), Faculty of
EEMCS, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands.

Email: j.h.bullee@utwente.nl

Search for more papers by this author
Lorena Montoya, 

Lorena Montoya

Services, Cyber-security, and Safety Group (SCS), Faculty of EEMCS, University
of Twente, PO Box 217, Enschede, 7500 AE The Netherlands

Search for more papers by this author
Wolter Pieters, 

Wolter Pieters

Faculty of Technology, Policy and Management, Delft University of Technology
P.O. Box 5015 2600 GA Delft

Search for more papers by this author
Marianne Junger, 

Marianne Junger

Faculty of Faculteit Behavioural, Management and Social Sciences, University of
Twente, P.O. Box 217,, 7500 AE Enschede

Search for more papers by this author
Pieter Hartel, 

Pieter Hartel

Faculty of Electrical Engineering, Mathematics and Computer Science, Delft
University of Technology, P.O. Box 5031 2600 GA Delft

Search for more papers by this author
Jan-Willem Hendrik Bullée, 

Corresponding Author

Jan-Willem Hendrik Bullée

 * j.h.bullee@utwente.nl

Services, Cyber-security, and Safety Group (SCS), Faculty of EEMCS, University
of Twente, PO Box 217, Enschede, 7500 AE The Netherlands

Correspondence

Jan-Willem Bullée, Services, Cyber-security, and Safety Group (SCS), Faculty of
EEMCS, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands.

Email: j.h.bullee@utwente.nl

Search for more papers by this author
Lorena Montoya, 

Lorena Montoya

Services, Cyber-security, and Safety Group (SCS), Faculty of EEMCS, University
of Twente, PO Box 217, Enschede, 7500 AE The Netherlands

Search for more papers by this author
Wolter Pieters, 

Wolter Pieters

Faculty of Technology, Policy and Management, Delft University of Technology
P.O. Box 5015 2600 GA Delft

Search for more papers by this author
Marianne Junger, 

Marianne Junger

Faculty of Faculteit Behavioural, Management and Social Sciences, University of
Twente, P.O. Box 217,, 7500 AE Enschede

Search for more papers by this author
Pieter Hartel, 

Pieter Hartel

Faculty of Electrical Engineering, Mathematics and Computer Science, Delft
University of Technology, P.O. Box 5031 2600 GA Delft

Search for more papers by this author
First published: 14 July 2017
https://doi.org/10.1002/jip.1482
Citations: 25
About


 * * FIGURES
   
   
   * REFERENCES
   
   
   * RELATED
   
   
   * INFORMATION
 * PDF

Sections
 * Abstract
 * 1 INTRODUCTION
 * 2 METHOD
 * 3 RESULTS
 * 4 DISCUSSION
 * ACKNOWLEDGMENTS
 * REFERENCES
 * Citing Literature

PDF
Tools
 * Request permission
 * Export citation
 * Add to favorites
 * Track citation

ShareShare

Give access

Share full text access
Close modal

Share full-text access

Please review our Terms and Conditions of Use and check box below to share
full-text version of article.
I have read and accept the Wiley Online Library Terms and Conditions of Use

--------------------------------------------------------------------------------

Shareable Link

Use the link below to share a full-text version of this article with your
friends and colleagues. Learn more.


Copy URL


Share a link

Share on
 * Email
 * Facebook
 * Twitter
 * LinkedIn
 * Reddit
 * Wechat




ABSTRACT

The aim of this study was to explore the extent to which persuasion principles
are used in successful social engineering attacks. Seventy-four scenarios were
extracted from 4 books on social engineering (written by social engineers) and
analysed. Each scenario was split into attack steps, containing single
interactions between offender and target. For each attack step, persuasion
principles were identified. The main findings are that (a) persuasion principles
are often used in social engineering attacks, (b) authority (1 of the 6
persuasion principles) is used considerably more often than others, and (c)
single-principle attack steps occur more often than multiple-principle ones. The
social engineers identified in the scenarios more often used persuasion
principles compared to other social influences. The scenario analysis
illustrates how to exploit the human element in security. The findings support
the view that security mechanisms should include not only technical but also
social countermeasures.




1 INTRODUCTION

Social engineering is the art of exploiting the weakest link in information
security systems (i.e., the people who use them; Bosworth, Kabay, & Whyne,
2014). The targets are deceived to release information or perform a malicious
action on behalf of the offender (Huber, Kowalski, Nohlberg, & Tjoa, 2009). This
paper focusses on the social influence techniques offenders use in social
engineering attacks to make their targets comply. Success stories from the
social engineering literature were analysed to answer the research questions.

Information security incidents are often caused by human failure (Chan, Woon, &
Kankanhalli, 2005), rather than technical failure (Schneier, 2000). Because
humans handle information systems, information security needs to take not only
the technical but also the human element into account. The attack on the human
element of security is called “social engineering.” This technique consists of
using social influences to convince people that the offender (e.g., social
engineer) is whom he claims or pretends to be. The offender takes advantage of
people to obtain information or knowledge one should not have (Gupta, Agrawal, &
Garg, 2011). Social engineering constitutes a security risk because it can be
used to bypass intrusion detection systems, firewalls, and access control
systems. One of the dangers of social engineering attacks is their harmless and
legitimate appearance so that targets are unaware of being victimised (The
Federal Bureau of Investigation, 2013; Hadnagy & Wilson, 2010). The result of a
social engineering attack can be disastrous (e.g., crippled corporate networks,
identity theft, or monetary loss; Gupta et al. ,2011).

Security experts have stated that as our culture becomes more dependent on
information technology and technical prevention improves, social engineering
will be the greatest threat to any security system Rouse (2006). Information
security has traditionally been treated as a technical problem, resulting in
information security teams being staffed solely by engineers (Rhee, Kim, & Ryu,
2009). This biased perspective of information security has led to the human
factor being underestimated.

The field of human error, in a group or organisational context, has been widely
researched (e.g., Chikudate, 2009; Edmondson, 1996; Zhao & Olivera, 2006). The
type of human error that relates to unintentional errors is called a “slip.”
Slips refer to failures in executing the behaviour as planned and are mainly
caused by attentional failure (Whittingham, 2004; Zhao & Olivera, 2006).
Examples of slips are (a) a cashier forgetting to apply the discount to one
product, (b) not properly closing a fire escape, or (c) leaving a USB key
containing a list of confidential data on the train. The individual knows how to
perform the task, has the intention to do it, but does not do it properly (Zhao
& Olivera, 2006). Another type of error is that induced by external parties with
the intention to make one fail a procedure (i.e., offenders using influencing
techniques to manipulate their targets into compliance). Examples are (a)
sharing credit card details with a stranger, (b) providing physical access to
someone without appropriate credentials, or (c) supplying information that is
needed for a spy to access the corporate network. The latter three examples
relate to social engineering attacks.

Social engineering attacks can be explained using the analogy of the stack of
Swiss cheese slices, known as the Swiss cheese model or the cumulative act
effect (Reason, 1990). This model depicts the various elements of an
organisation as layers. In an ideal world, these layers are intact; however, in
the real world, they resemble slices of cheese with holes. A single layer that
has a hole poses no problem. However, if there are holes in multiple layers and
these align, an error can take place, that is, the system is penetrable, and
therefore, an employee could become a victim of social engineering. Offenders
can use influence techniques to create holes in the cheese or to align them.

This study investigates the errors induced by external parties, in the context
of information security. Following the analogy of the Swiss cheese model, this
study aims to identify the number, characteristics, and alignment of cheese
slices (i.e., attack steps), which led to successful social engineering attacks
(i.e., system failure).

From a psychological point of view, social engineering is part of decision
making. Because people do not have the cognitive capacity to process all
information, decision making involves using rules of thumb (i.e., heuristics;
Cialdini, 2009). These mental shortcuts (resulting from experience and genetics)
work well in most circumstances. However, when a heuristic goes wrong, a
cognitive bias occurs (Gigerenzer, 1991; Tversky & Kahneman, 1974). Social
engineers (i.e., the offenders) are well aware of the flaws in human logic and
nudge the heuristics of their targets into systematic errors (i.e., cognitive
biases) to make them comply (Bosworth et al., 2014; Dang, 2008; Kennedy, 2011;
Luo, Brody, Seazzu, & Burd, 2011; Twitchell, 2009).

Studies on traditional crime have analysed both offenders and victims. However,
in computer-related crime, it is difficult to find offenders for research
purposes. In criminology, it is common to analyse the crime from the perspective
of the targets themselves. Information extraction techniques such as interviews
or questionnaires can be used to get details about the crime. On the other hand,
it is harder to get the the offender's point of view, which is especially the
case when the target is unaware of being victimised because the offender is
unknown to him. This study aimed to gain an insight into social engineering
attacks from an offender's perspective, and the sources used are accounts by
social engineers describing social engineering scenarios. The central question
in this paper is how are social influences successfully used by social engineers
to persuade their targets to comply with their requests?

A typical example of a social engineering attack from The art of deception:
Controlling the human element of security(Mitnick & Simon, 2002):

> “Hi,” says the voice at the other end of the line. “This is Tom at Parkhurst
> Travel. Your tickets to San Francisco are ready. Would you like us to deliver
> them, or would you like to pick them up?” “San Francisco?” says Peter. “I'm
> not going to San Francisco.” “Is this Peter Abels?” “Yes, but I don't have any
> trips coming up.” “Well,” the caller says with a friendly laugh, “Are you sure
> you don't want to go to San Francisco?” “If you think you can talk my boss
> into it…” says Peter, playing along with the friendly conversation. “Sounds
> like a mix-up,” the caller says. “On our system, we book travel arrangements
> under the employee number. Maybe somebody used the wrong number. What's your
> employee number?” Peter obligingly recites his number.

From this social engineering example, it is clear that the caller tricks the
employee into disclosing his employee number. By having this small piece of
specific information, one has knowledge that can be used to mimic an insider. By
using a small lie, the caller made the employee fail to execute the “correct”
behaviour (which in this case would be to callback the travel agency on a known
number).

The first step in unravelling this complex topic is to find out how an
individual can be persuaded to comply with malicious requests from offenders. By
analysing offender accounts, we aim to find commonly used methods in social
engineering attacks.


1.1 PRINCIPLES OF PERSUASION

Once a person is a target, the offender can use social influences to change the
odds of compliance in his favour. Compared to gullibility (i.e., the willingness
to believe someone or something in the absence of reasonable proof; Greenspan,
2008), persuasion is a property of the offender, rather than of the target. A
subset of six social influences (referred to as persuasion principles) were
investigated by Cialdini (2009): authority, conformity, reciprocity, commitment,
liking, and scarcity.

Authority is the principle that describes people's tendency to comply with the
request of authoritative figures. If people are unable to make a thorough
decision, the responsibility to do so is transferred to the group or someone
they believe is in charge. Crisis and stress activate the behavioural trait of
responsibility transition.

Conformity, or social proof, is the act of imitating the behaviour of other
people. Members of the in-group have a stronger feeling of group safety compared
with members of the out-group (Asch, 1951).

Reciprocity refers to the giving of something in return. The target feels
indebted to the requester for making a gesture and even the smallest gift puts
the requester in an advantageous position.

Commitment refers to the likelihood of sticking to a cause or idea after making
a promise or adhesion. In general, when a promise is made, people will honour
it, which increases the likelihood of compliance (Cialdini, 2009).

Liking someone puts that person in a favourable position. People tend to like
others who are similar in terms of interests, attitudes, and beliefs.

Scarcity occurs when a product, service, or information has limited
availability. People therefore perceive an increased value and attractiveness
towards these products which makes them more desired than others.


1.2 EFFECTIVENESS OF PERSUASION PRINCIPLES

Persuasion principles have been researched for several decades, and there is
empirical evidence that shows their effectiveness. Below, we present a short
overview of meta-analyses related to each persuasion principle.

The most famous study that illustrated authority is the classical shock
experiment performed by Stanley Milgram (1963). Sixty-six percent of the
participants did not hesitate to deliver a deadly dose of 450 V to a human test
subject, which they were instructed to perform by a man they believed to have
legitimate authority. An evaluation of 23 replication studies, conducted over
the past 35 years, studied the obedience to authority paradigm. Almost half of
the studies (i.e., 11 studies) showed a lower rate of obedience compared to the
initial study by Milgram, ranging from 28% to 65%. The remaining 12 studies
showed an equal or higher rate of obedience, ranging from 66% to 91% (Blass,
1999). Although the studies found different rates of obedience, it can be
concluded that authority is an important behavioural phenomenon.

In 1965, Salomon Asch conducted an experiment on the effects of conformity. One
of the outcomes was that 75% of the participants followed the majority, even
when the majority stated an incorrect answer. This study was replicated many
times in various contexts. A meta-analysis on conformity, containing 133 studies
showed it to be effective (Bond & Smith, 1996). The level of conformity depends
on the number of people (i.e., size of the majority) displaying a certain
behaviour and can be estimated as where . In this function, I is the level of
conformity, and N the majority size (Tanford & Penrod, 1984).

Reciprocity can be illustrated by means of reciprocal concessions, also known as
the “door-in-the-face” technique (DitF). Compliance is the result of first
rejecting the extreme initial request and then asking for a moderate
alternative. The requester changes the initial request, whereas the receiver
feels inclined to change as well, resulting in the change from a “no” to a “yes”
(Cialdini et al. 1975). A meta-analysis (k=22 studies, N=3,164 subjects) showed
that the DitF technique is effective. Those in the DitF group have higher odds
of complying than those in the control group (Pascual & Guéguen, 2005).

Commitment is sometimes referred to as the “foot-in-the-door” (FitD) technique.
Once a person has been induced to comply with a small request, he or she is more
likely to comply with a larger demand (Freedman & Fraser, 1966). A meta-analysis
(k=22, N=3,124) showed that the FitD technique is effective. Those in the FitD
group have higher odds of complying than those in the control group (Pascual &
Guéguen, 2005). The mechanisms behind DitF and FitD are diametrically opposed. A
comparison (k=22, N=3,192) to find out which technique is more effective showed
that both are equally effective (Pascual & Guéguen, 2005).

The effect of liking on self-disclosure has been investigated extensively, in
particularly the question: “Do we disclose more to people we like?” A
meta-analysis (k=31) showed that people indeed have the tendency to disclose
more personal information to people they like. Furthermore, there is little
evidence that females and males differ in this respect (Collins & Miller, 1994).

Unlike the other principles, no meta-analysis was found for the scarcity
principle; therefore, an individual study is discussed. Scarce products have an
increased perceived value. The idea of not having something or a potential loss
plays an important role in human decision making. Health researchers
demonstrated this effect in a study involving breast cancer awareness pamphlets.
The pamphlets stating the potential losses of not screening had significant more
effect than pamphlets stating what the potential gain was (Meyerowitz & Chaiken,
1987).

The effect of scarcity was compared to conformity and a control condition,
involving 153 university students in two emotional states: (a) fear and (b)
romance. Results showed that (a) fear-state conformity appears to be more
persuasive than the control condition (nonconformity), (b) fear-state scarcity
appears to be less persuasive than the control condition (nonscarcity), (c)
romance-state scarcity appears to be more persuasive than the control condition
(nonscarcity), and (d) romance state conformity appears to be less persuasive
than the control condition (nonconformity). Thus, fear improves the effect of
conformity and romance improves the effect of scarcity (Griskevicius et al.
2009).

For a summary of meta-analytical findings, refer to Table 1. The p value
indicates whether the principle was effective compared to the controls. This was
the case for the conformity, reciprocity, commitment, and scarcity principles.
For authority and liking, no such statistic was reported in the literature.

Table 1. Overview of meta-analyses scores for each persuasion principle

Principle N ke Complianced Statistic pa Reference Authority 1,041b 23 62.5
[28–91] – – (Blass, 1999) Conformity 4,627 133 28.8 [2.1–60.1] d=.92 .001 (Bond
& Smith, 1996) Reciprocity 3,164 22 41.1 [3.2–84.5] t(21)=2.26 .03 (Pascual &
Guéguen, 2005) Commitment 3,124 22 45.2 [3.2–100] t(21)=2.71 .01 (Pascual &
Guéguen, 2005) Liking – 31 – d=.717 .05 (Collins & Miller, 1994) Scarcityc 311 1
– F(1,305)=5.34 .021 (Griskevicius et al. 2009) Reciprocity versus 3,192 22 –
t(21)=0.1 ns (Pascual & Guéguen, 2005) commitment

 * Note. – = Not Available; ns = not significant.
 * aThe p-value tests whether the principle was effective in relation to the
   controls.
 * bN estimated by author of the present study based on available studies.
 * cOperationalised as romance.
 * dAverage unweighed percentage of compliance [the number between brackets
   indicates the min and max].
 * ek indicates the number of studies included in the meta-analysis.



Based on Table 1, the persuasion principles were ranked on the basis of the
compliance rate (i.e., effectiveness): (a) authority, (b) commitment, (c)
reciprocity, and (d) conformity. Authority is therefore the persuasion principle
with the strongest effect.

Persuasion principles seem to be effective, although none of the studies found
focussed on the IT context. This research aims to answer the question: How are
social influences successfully used by social engineers to persuade their
targets to comply with their requests? One expectation was that in social
engineering attacks, some persuasion principles would be used more often than
others.


1.3 MODALITY AS MODERATOR OF PERSUASION

Social engineering is often associated with, but not limited to, calling a
target and asking for a password (Winkler & Dealy, 1995). However, research on
persuasion principles in the psychology literature shows that they are sometimes
used over the telephone, but sometimes they are used face to face. An overview
of differences in modality is presented below.

The influence of modality is illustrated in a meta-analysis on the DitF
persuasion strategy. This study compared (k=56) studies using the face-to-face
modality with (k=31) studies using the telephone modality. The combined result
of N=7,641 subjects, showed no statistical difference between the two (O'Keefe &
Hale, 2001).

A meta-analysis on modality found no effect on compliance for both verbal (k=78,
N=7,138) and behavioural (k=39, N=3,125) compliance (Feeley, Anker, & Aloe,
2012). Verbal compliance refers to saying that you will do something, whereas
behavioural compliance to actual doing so. This means that modality does not
“moderate” the relationship between strategy and compliance.

In a variation of the Milgram experiment (refer to Section 1.2), the authority
(i.e., experimenter) left the room and gave instructions via the telephone. The
results are an obedience rate of 20.5%, a significantly lower outcome compared
to the 66% for the face-to-face condition (Milgram, 1965; 1974). The power of
the authority seems to drop severely when there is no face-to-face contact.

The influence of modality was tested on a combination of product judgement
(i.e., recall, attitude, and behavioural intentions) and type of goods (i.e., a
product or a service) offered for sale (Szymanski, 2001). The product and the
service were both presented via a face-to-face or telephone modality. The
telephone modality had statistically significant higher scores (i.e., more
influence) compared to the face-to-face modality. For goods, on the other hand,
no difference was found in modality for behavioural intentions (Szymanski,
2001).

The results show that for some persuasion principles, modality moderates the
relation between request and compliance, refer to Table 2. These mixed outcomes
also indicate that there are other variables of influence and that the
operationalisation is important.

Table 2. Overview of meta-analytical scores face to face/telephone

Principle Moderator N kb pa Reference Authority – 80 1 <.001 (Milgram, 1965)
Reciprocity (DitF) – 7,641 87 ns (O'Keefe & Hale, 2001) Reciprocity (DitF)
Verbal 7,138 78 ns (Feeley et al. 2012) Reciprocity (DitF) Behavioural 3,125 39
ns (Feeley et al. 2012) Sales presentation Goods 146 1 <.05 (Szymanski, 2001)
Sales presentation Service 114 1 ns (Szymanski, 2001)

 * Note. DitF = door-in-the-face; −= Not Available; ns= not significant.
 * aThe p value tests whether the principle was effected by the modality.
 * bk indicates the number of studies included in the meta-analysis.



1.3.1 APPLYING PERSUASION PRINCIPLES TO BYPASS SECURITY

Research on persuasion principles is commonly associated with the social
sciences (e.g., refer to Blass, (1999); Bond & Smith, 1996; Pascual & Guéguen,
2005; Collins & Miller, 1994). We next provide an example to illustrate how an
offender could use each persuasion principle in an IT-related office environment
setting:

Authority. An offender claims that he works in the IT department or that he is
an executive in the company (Mitnick & Simon, 2002).

Conformity: The offender calls a target, says that he is conducting a survey,
and names other people from the organisation who already participated. The
survey embeds a series of questions that draw the victim into revealing the
username and password.

Reciprocity: The offender calls a target and identifies himself as an employee
from the IT department. The offender explains that there was a computer virus
and that some data servers have to be restored. It would help the employee, if
the target provides the password. The target is more likely to reciprocate
because the caller offers him help.

Commitment: An employee is called from the finance department and asked for
something small. The employee is called again later and asked for something
bigger; this process is continued until the goal is reached.

Liking: An offender acts friendly, gives compliments, and states that he studied
at the same university as the target hence emphasising similarities.

Scarcity: A call centre employee rings and gives a fake sales pitch. The target
is not interested and wants to hang up the phone, but the offender rapidly
mentions that the first 100 people who register on a given website will win two
vouchers for a particular event

These six short scenarios are examples of how an offender can influence a
target. The offender can use the six principles of persuasion to achieve a
higher probability of compliance.


1.4 CRIME SCRIPTS

Understanding how offenders use social influences to convince their targets to
comply is a key element in dissecting social engineering attacks. To dissect an
attack into steps, we use the concept of the “crime script.” Crime scripts
relate to “attack templates,” and in technical research areas, crime scripts are
referred to as “attack life cycles” (Marconato, Kaaniche, & Nicomette, 2012).
Cornish (1994) argued that crime scripts can be used to understand how a crime
is executed. Crime scripts consist of sequential “script functions” and
accompanying “script actions.” These scripts organise the knowledge and
understanding of the routine behavioural process: preconditions, initiation,
actualisation, doing, and postconditions (Cornish, 1994). Breaking down crimes
into small steps increases the comprehension of the crime as a whole. Each step
in the crime script resembles a slice in the Swiss cheese model. However, this
is not necessarily a one-to-one relationship because the Swiss cheese model
relates to defender mechanisms; and it is possible that an offender bypasses
several defence layers at once using a single attack step (or vice versa).
Moreover, this dissection is useful for designing specific interventions.

Crime scripts have already been developed many times, for example, in the field
of resale of stolen vehicles (Tremblay, Talon, & Hurley, 2001), organised crime
(Rowe, Akman, Smith, & Tomison, 2012), illegal waste activity (Thompson &
Chainey, 2011), drug manufacturing (Chiu, Leclerc, & Townsley, 2011), and serial
sex offences (Beauregard, Proulx, Rossmo, Leclerc, & Allaire, 2007), whereas
templates were used to identify rapists' target selection patterns (Beauregard,
Rebocho, & Rossmo, 2010). However, to the best of our knowledge, there is no
crime script analysis on social engineering attacks from the viewpoint of the
offender. We therefore investigate the social influences used by an offender in
a social engineering attack.


1.5 EXPERIMENTAL CONTEXT

Literature shows that social engineering works (Mann, 2008), that it is
effective (Schellevis, 2011), and that targets are often unaware of being
victimised (The Federal Bureau of Investigation, 2013; Hadnagy & Wilson, 2010).
However, there is limited information available on the inner working of such
attacks. Penetration testing reports occasionally surface, but these represent
the proverbial needle in a haystack and are “uncontrolled” in the statistical
sense. Books on social engineering (Hadnagy & Wilson, 2010; Mann, 2008; Mitnick
& Simon, 2002; Mitnick, Simon, & Wozniak, 2011) provide an insight into how
successful social engineering attacks are executed. To the best of our
knowledge, no studies exist that identify social influences in social
engineering attack scenarios.

Therefore, in this paper, social engineering cases are dissected to find out
what social influences are used.


1.6 RESEARCH QUESTION

The objective of the present research was to find out “How are social influences
successfully used by social engineers to persuade their targets to comply with
their requests?” Four questions and subquestions were formulated:
 * Q1. “What modality is used to execute social engineering attacks?”
 * Q2. “Which persuasion principles are used in the context of social
   engineering attacks?”
 * Q3. “How are the persuasion principles combined within a single step in
   social engineering attacks?”
 * Q3.1. “How many persuasion principles are used in an attack step?”
 * Q3.2. “How many attack steps are used in a crime script?”
 * Q3.3. “How are persuasion principles used in the course of a crime script?”
 * Q4. “What is the consistency among persuasion principles between two steps in
   the crime script?”
 * Q4.1. “Do principles differ over the course of a crime script?”
 * Q4.2. “How related are two consecutive attack steps within a crime script?”
 * Q4.3. “How related are the first and last step of a crime script?”


2 METHOD


2.1 DATA SELECTION

Goodreads is a social cataloging website where book lovers can review, rate, and
catalogue what they have read. It currently contains 900 million books and 34
million reviews. There are over 100 books on Goodreads' bookshelf related to
social engineering. *The following book inclusion criteria were used: (a) Social
engineering involves a nontechnical social attack against the operator of a
computer system, and (b) the book contains case studies illustrating the use of
social engineering. The top four of books most often identified as social
engineering by the community of Goodread members and met the two inclusion
criteria were included in the analysis: (a) The art of deception: Controlling
the human element of security (Mitnick & Simon, 2002), (b) Ghost in the Wires:
My Adventures as the World's Most Wanted Hacker” (Mitnick et al. 2011), (c)
Hacking the Human: Social Engineering Techniques and Security
Countermeasures(Mann, 2008), and (d) Social Engineering: The Art of Human
Hacking (Hadnagy & Wilson, 2010).

According to Scopus †, the four books together are cited 240 times in scientific
publications: 206, 8, 6, and 20 times. Compared to books written by other
computer hackers, only The Art of Deception can be considered as highly cited
(ie, 206 times), whereas Social Engineering: The Art of Human Hacking can be
considered as moderately cited. The story of Richard Jones is told in
Underground: Tales of Hacking, Madness and Obsession on the Electronic Frontier”
(Dreyfus & Assange, 2012) and was cited 7 times. The memoires of Julian Assange,
as in Julian Assange: The Unauthorised Autobiography (Assange, 2011) is cited 4
times. Former black hat hacker Kevin Poulsen wrote the book Kingpin: How One
Hacker Took Over the Billion-Dollar Cybercrime Underground (Poulsen, 2011),
which is cited 8 times.

In each book, in the analysis, social engineering is illustrated by means of
success scenarios, executed by the authors, their friends, or other
professionals from the field. The present analysis includes only scenarios that
contain interactions between at least two humans. Scenarios that consist only of
pure hacking, such as obtaining access to information via an open port on the
server found using a port scanner were excluded because these lack human
interaction. In addition, we excluded forms of threatening such as blackmailing
and other human forms of interactions such as bribing, as we do not consider
these to constitute social engineering. What is considered as social engineering
is the use of deception and manipulation of the human element to release
information to the offender (Bosworth et al. 2014; Dang, 2008; Huber et al.
2009). In total, there were 74 social engineering scenarios extracted for the
analysis.

2.1.1 QUALITY OF THE BOOKS AND ECOLOGICAL VALIDITY (I.E., REALISM)

An internet search was performed to assess the quality of the four books and
their ecological validity (i.e., their degree of realism). The ratings of the
four books found in three on-line sources (i.e., books.google.com, amazon.com,
and goodread.com) were analysed. The ratings show that more than 70% of the
readers rated the books as being either good or very good. Some of the scenarios
that originate from The Art of Deception: Controlling the Human Element of
Security” were described as fictionalised (Mitnick & Simon, 2002). For the other
three books, there was no evidence found about either fabrication or
fictionalisation of stories, based on the book reviews at Goodreads and Amazon.

In an attempt to obtain more insight into the extent to which scenarios in The
Art of Deception were fictionalised, the online legal research database Westlaw
was queried. The results show that Kevin Mitnick was convicted two times: the
first time in 1988 and the second time in 1996. In 1988, he was charged with
“possession of unauthorised access devices” (in violation of 18 Code of Laws of
the United States of America (U.S.C.) section 1029(a)(3)) and computer fraud (in
violation of 18 U.S.C. section 1030(a)(4)). He pled guilty and was sentenced to
12 months in prison followed by a 3-year period of supervised release under
special conditions. The company where the computer fraud was performed is
mentioned in the book The Art of Deception (Mitnick & Simon, 2002); however,
there are insufficient details in the court documents to validate the method
(USA v. Mitnick, 1998). In February 1995, Mitnick was charged with “access
device fraud” (in violation of 18 U.S.C. section 1029) and computer fraud (in
violation of 18 U.S.C. section 1030). A 25 count indictment against him alleging
“computer fraud,” “wire fraud,” and “interception of wire communications”
relating to additional alleged illegal conduct by him was presented in September
1996. This indictment contains a list of organisations, which are mentioned in
the scenarios used in Ghost in the Wires (Mitnick et al. 2011). Similarly, no
details were found in the court documents to validate the method (USA v.
Mitnick, 1996). The court documents obtained via the Westlaw online legal
research service provided no additional insight into the scenarios. What was
therefore found from this validation investigation was that some of the
companies mentioned in the books' scenarios also appear in the indictments,
therefore, it seems plausible that the book The Art of Deception is not a work
of fiction.


2.2 READERS

All 74 scenarios were independently coded by two researchers. The first
researcher (i.e., the first author) is a 29-year-old male PhD candidate with a
background in both psychology and computer science. The second researcher is a
22-year-old female student assistant with a background in information and
communication sciences. An interrater reliability analysis using the κ statistic
was performed to determine the consistency among researchers.


2.3 PROCEDURE

To ensure agreement between the researchers, they both (a) processed a
description of the persuasion principles, (b) performed coding on a test dataset
of five scenarios, and (c) discussed the outcome of the training results. The
description of the principles was the same as that of Section 1.1. The set of
training scenarios was a random selection from all scenarios.

After the training, both readers agreed that analysing a scenario as a whole
(refer to Figure 1) would bias the results, because multiple people can be
involved and an offender can approach each individual differently. Therefore, it
was decided to split the scenarios into attack steps, each containing a single
interaction between two individuals. For example, if the offender first talked
to employee A and next to employee B and finally to employee C, the scenario is
split into three attack steps (refer to Figure 2). The persuasion principles
used by the offender were coded for each attack step (refer to Figure 3). Figure
3 shows three interactions containing one, two, and two persuasion principles.
All the scenarios were coded twice, meaning that the work was not split and
concatenated afterwards but that instead, the resulting dataset consists of
consensual results. After coding all attack steps, the interrater agreement was
calculated. The scores of both readers were compared to generate the final
dataset. If both readers identified the same principles for a given attack step,
there was consensus. However, when there was a difference in the codes, the
readers discussed the different views and came to a conclusion (the majority of
differences related to one coder accidentally marking the wrong principle).

Figure 1
Open in figure viewerPowerPoint
One scenario
Figure 2
Open in figure viewerPowerPoint
Three attack steps
Figure 3
Open in figure viewerPowerPoint
Five persuasion principles

Figure 4 shows the dissection of a “real” scenario from Mitnick and Simon
(2002). The scenario contains two attack steps, where each attack step contains
one persuasion principle. In both attack steps 1 and 2, the offender uses
impersonation together with the authority principle. In attack step 1, this was
achieved by claiming to be an attorney, whereas in attack step 2, by claiming to
be a staff member from the R&D department. In both attack steps, authority was
operationalised by means of titles.

Figure 4
Open in figure viewerPowerPoint
Example: one scenario, two attack steps, and two persuasion principles


2.4 VARIABLES

There are two kinds of variables in the analysis, those related to (a) the crime
script and (b) the attack step. The variables related to the crime script are
“modality” and “steps.” The variables related to the attack step are “persuasion
principles” (six variables), “other,” “first/last,” and “former/latter.”

The six dichotomous (persuasion principle) variables were dummy coded as
0=notused and 1=used. In case none of the six persuasion principles seemed
appropriate, the variable other recorded other social influence tactics the
offender used to deceive the target. The variable was a string variable hence
allowing an open-ended response. In the open-ended responses, there was one
suggestion given related to “overloading.” Overloading can be used while
conducting a questionnaire by putting the trick question between other
questions. Due to the amount of information the brain has to process, there is a
transition to a passive mental state, in which information is absorbed rather
than evaluated (Janczewski & Colarik, 2008).

The modality variable was a string variable recording the modality used by the
offender (e.g., face to face or telephone).

The steps variable was an integer recording the number of attack steps in each
crime script (i.e., 1 means that there was a single attack step in the crime
script).

The categorical variables first/last contained the persuasion principle(s) used
in the first and last attack steps of a crime script.

The categorical variables former/latter contained the persuasion principle(s)
used in a chronological attack step pair of a crime script.


2.5 ANALYSIS

The first question (i.e., What modality is used to execute social engineering
attacks?) involves comparing the frequencies of different modalities to perform
social engineering attacks. The variable modality was tested using cross
tabulation and chi-square analysis. ‡

The second question (i.e., Which persuasion principles are used in the context
of social engineering attacks?) involves the frequencies of persuasion
principles used. The variable persuasion principles was recoded into a single
variable (i.e., an entry for each occurrence of the persuasion principle) and
was tested using Fisher's exact test. §

The third question (i.e., How are the persuasion principles combined within a
single step in social engineering attacks?) contains three subquestions: (a)
“How many persuasion principles are used in an attack step?”, (b) “How many
attack steps are used in an crime script?”, and (c) “How are persuasion
principles used in the course of a crime script?” The aim of the question is to
get an insight in how social engineering attacks are executed, which is relevant
for developing countermeasures. The first subquestion involves the variable
persuasion principles, which was recoded into a new variable containing the
number of persuasion principles used for each attack step and it was tested
using Fisher's exact test.§. The second subquestion compares path lengths using
the steps variable, and it was tested using Fisher's exact test.§ The third
subquestion involves the variables persuasion principles and steps, and it was
tested using Fisher's exact test.§ In total, there were four analyses performed,
one for each persuasion principle (except for scarcity and conformity due to
insufficient observations).

For the fourth question, (i.e., What is the consistency among persuasion
principles between two steps in the crime script?) contains three subquestions:
(a) “Do principles differ over the course of a crime script?”, (b) “How related
are two consecutive attack steps within a crime script?”, and (c) “How related
are the first and last step of a crime script?” These subquestions enable a
better understanding of the crime scripts. The first subquestion provides an
insight into the use of persuasion principles at different stages of the attack
and involves the variables persuasion principle and steps. The variable
persuasion principle was recoded as 0 = not using persuasion principle and
1 = using persuasion principle. This was tested using cross tabulation and
chi-square. The second and third subquestions are used to analyse changes in
tactics at a microattack level. The second subquestion compares two consecutive
attack steps. It involves the variables former/latter, and it was tested using
Fisher's exact test.§ The third subquestion compares the first attack step with
the last using the variables first/last. This was tested using Fisher's exact
test.§ Ultimately these analyses enable to find out whether the offender's
principle selection is drawn at random or not, which would influence the design
of awareness campaigns by security managers.

For an overview of all variables used in the different tests, refer to Table 3.

Table 3. Overview of variables and statistical test.

Assumptions Questiona Variableb Ideal testc Indd Obse Applicable testf Q1
Modality chi-square Y N Fisher's exact Q2 Persuasion principles chi-square Y N
Fisher's exact Q3.1 Persuasion principles chi-square Y N Fisher's exact Q3.2
Steps chi-square Y N Fisher's exact Q3.3 Steps (authority) chi-square Y N
Fisher's exact Q3.3 Steps (commitment) chi-square Y N Fisher's exact Q3.3 Steps
(liking) chi-square Y N Fisher's exact Q3.3 Steps (reciprocity) chi-square Y N
Fisher's exact Q4.1 Persuasion principles chi-square Y Y chi-square Q4.2
Former/latter chi-square Y N Fisher's exact Q4.3 First/last chi-square Y N
Fisher's exact

 * aThis column refers to the specific question and subquestion.
 * bThis column refers to the variables that were used in the statistical test.
 * cIdeal test refers to which test ideally to use if all the assumptions were
   met.
 * dInd refers to the independence assumption that in required for some tests.
 * eObs refers to the minimal number of observations that is required for some
   tests.
 * fThe applicable test given the assumption results.



In this study, the focus is on the “execution” phase of the crime script, which
follows the preparation and target selection phases. All the interactions (i.e.,
attack steps) found in the 74 scenarios were annotated with a time component to
keep track of the chronological order.


3 RESULTS


3.1 DESCRIPTIVE STATISTICS

Seventy-four scenarios were analysed. This work resulted in the identification
of 142 attack steps containing 180 occurrences of persuasion principles. Out of
the 142 attack steps, 125 used persuasion principles whereas 17 involved other
social influences. The number of attack steps containing persuasion principles
is statistically different from 0, χ2(1,N=142)=49.5, p<.001. This means that
there is a difference between the scenarios that use persuasion principles and
the group that does not use them. The category of “other social influences”
covers 12% of all social influences used by offenders in their attack steps.
This category contains: (a) act ignorant 1× (5.9%), (b) creating curiosity 2×
(11.8%), (c) distracting 1× (5.9%), (d) empathy/pity 2× (11.8%), (e) just ask
for it 9× (52.9%), and (f) overloading 2×(11.8%).

All attack steps (i.e., interactions) are summarised in Table 4, which shows
where the scenario originated from. Table 4 also shows that (a) authority as a
single principle is the most commonly used attack step; it is used in 76 (53.5%)
of all attack steps, and it is identified in all six steps over time; (b) double
principles (i.e., using two principles in one attack step) include authority in
all 27 (100%) attack steps; (c) liking was used in 10 (91%) of the cases, which
use three persuasion principles in an attack step; (d) both commitment,
conformity, and reciprocity are only executed once as single principles; (e) the
most frequently used attack path is (a) Authority - (b) Authority - Compliance.
All crime scripts and attack steps listed on Table 4 are summarised in a
single-tree structure (refer to Figure fig:Forest). The attack steps containing
similar strategies (i.e., persuasion principles) at the same point in time are
merged into a single node in the tree. This tree gives an overview of all the
social engineering scenarios from the books and shows the frequent and less
frequent attack paths. There are other studies using multiple crime scripts for
generalisation purposes, for example, on the topic of wildlife trafficking
(Lavorgna, 2014). However, this is the first study that combined multiple crime
scripts into a single visualisation.

Table 4. Combination of principles found in books

Principles Where to find Freq OTHER - Comply 1:[47, 6, 16, 36, 30] 5× OTHER -
OTHER -Auth - Comply 1:[2] 1× OTHER -Auth - Comply 1:[37, 11] 2× OTHER -Auth -
Auth - Auth Reci Comm - Auth - Comply 3:[5] 1× OTHER - Auth Comm - Auth - Auth -
Auth Reci Like - Comply 2:[4] 1× OTHER -Auth - Auth Reci - OTHER - Comply 1:[27]
1× OTHER - Like - Comply 2:[16], 4:[2] 2× Auth - Comply 1:[5, 10, 12, 17, 21,
22, 25, 29, 35, 41, 45, 46], 15× 2:[12, 14], 3:[3] Auth - Auth - Comply 1:[1,
26, 38, 44, 49], 2:[1, 11], 3:[1] 8× Auth - Auth - Auth - Comply 1:[28,40] 2×
Auth - Auth - Auth - Auth - Auth - Comply 2:[18] 1× Auth - Auth - Auth Comm -
Comply 2:[13] 1× Auth - Auth - Auth Comm - Auth Comm - OTHER -Auth - Comply
1:[34] 1× Auth - Auth - Auth Like - Comply 2:[5] 1× Auth - Auth - Auth Reci -
Auth - Auth - Auth Reci - Comply 2:[8] 1× Auth - Auth - Reci Comm Like - Comply
4:[1] 1× Auth - Auth Reci - Comply 2:[10] 1× Auth - Auth Reci Like - Comply
1:[14] 1× Auth Comm - Comply 1:[8, 23] 2:[6] 3× Auth Comm - Auth - Like - Auth
Like - Comply 1:[3] 1× Auth Comm Like - Comply 3:[2] 1× Auth Comm Like - Auth -
Auth - Comply 2:[7] 1× Auth Comm Like - Auth - Auth Reci - Auth - Comply 2:[9]
1× Auth Comm Like - Auth Comm Like - Comply 1:[9] 1× Auth Comm Like Scar -
Comply 2:[17] 1× Auth Conf Comm Like - Auth - Comm - Auth - Auth - Comply 4:[3]
1× Auth Like - Comply 1:[48], 2:[15], 3:[6] 3× Auth Like - Auth - Comply 2:[3]
1× Auth Reci - Comply 1:[7, 15, 24, 39], 2:[2], 3:[4] 6× Auth Reci - Auth -
Comply 1:[13] 1× Auth Reci - Conf - Comply 1:[18] 1× Auth Reci Like - Comply
1:[32] 1× Like - Comply 1:[4, 20] 2× Like - OTHER - Comply 1:[43] 1× Reci -
Comply 1:[31] 1× Reci Comm Like - Comply 4:[4] 1× Total 74×

 * Note. The left-most principle constitutes the initial step in the attack.
 * Auth: In more than half of the attack steps, authority was used as single
   step.
 * Auth Reci: All 27 double principle scenarios contained authority.
 * Auth Reci Like: Liking is used in 91% of the triple principle scenarios.
 * Reci: Commitment, conformity, and reciprocity are only executed once as
   single principle.
 * OTHER: Seventeen occurrences being nonpersuasion principles




3.2 INTERRATER AGREEMENT

The researchers' interrater reliability was κ= .909 (p<.000), 95% confidence
interval [.874, .944], N=852. The N represents 142 attack steps times six
possible persuasion principles per step. The results indicate that there is an
almost perfect agreement between the two researchers (Landis & Koch, 1977).


3.3 Q1: “WHAT MODALITY IS USED TO EXECUTE SOCIAL ENGINEERING ATTACKS?”

Out of the 142 attack steps, 123 (86.6%) were executed via telephone, and 18
(12.7%) were executed face to face and once via chat. There was a statistically
significant difference in the modality used in executing persuasion principles
in social engineering attack steps, χ2(1,N=142)=43.983, p=.000. Regarding
modality of attack steps, the telephone modality was used considerably more
often, but attack steps containing other means considerably less often.


3.4 Q2: “WHICH PERSUASION PRINCIPLES ARE USED IN THE CONTEXT OF SOCIAL
ENGINEERING ATTACKS?”

Fisher's exact test showed that there was a significant difference in the use of
principles during social engineering attacks, p=.000. The occurrence of the six
persuasion principles is (a) 63% for authority, (b) between 10% and 13% for
liking, reciprocity, and commitment, and (c) under 2% for scarcity and
conformity (refer to Figure 5).

Figure 5
Open in figure viewerPowerPoint
Persuasion principles used


3.5 Q2: “HOW ARE THE PERSUASION PRINCIPLES COMBINED IN SOCIAL ENGINEERING ATTACK
STEPS?”

3.5.1 Q3.1: “HOW MANY PERSUASION PRINCIPLES ARE USED IN AN ATTACK STEP?”

In total, 142 attack steps contain social influences; of which, 125 include
persuasion principles, and the remaining 17 contain some other social influence.

Single attack steps contain up to four persuasion principles. The average number
of persuasion principles used per attack step is M=1.44(SD=.723). There was a
statistically significant difference in the number of occurrences of persuasion
principles used in a single social engineering attack step, p=.000.

Regarding simultaneously used principles, single principles are used
considerably more often whereas quadruple principles considerably less often,
refer to Figure 6.

Figure 6
Open in figure viewerPowerPoint
Number of principles used per interaction

3.5.2 Q3.2: “HOW MANY ATTACK STEPS ARE USED IN AN CRIME SCRIPT?”

In total, 74 scenarios contain 142 attack steps. The shortest attack path
contained a single step, whereas the longest attack path consisted of six attack
steps. On average, the attack path has M=1.92(SD=1.311) steps. There was a
statistically significant difference in the number of attack steps used in crime
scripts, p=.000. Regarding combining attack steps, single step attacks are used
considerably more often, but attacks containing six steps considerably less
often, refer to Figure 7.

Figure 7
Open in figure viewerPowerPoint
Number steps in an attack

3.5.3 Q3.3: “HOW ARE PERSUASION PRINCIPLES USED IN THE COURSE OF A CRIME
SCRIPT?”

The combined principles were decomposed to obtain the occurrence of each
principle (for absolute occurrences refer to Figure 8 and for relative
occurrences to Figure 9). In the first step, before compliance, there were 101
occurrences of persuasion principles; in the second step, this decreased to 38,
whereas in the sixth step before compliance, there were only two occurrences.
There was a statistical significant difference in the use of authority (p=.000),
liking (p=.005), commitment (p=.003), and reciprocity (p=.002) over time.
Authority, liking, commitment, and reciprocity are used considerably more in the
first step before compliance, but these are used considerably less in the sixth,
fifth, and fourth step before compliance. Due to the limited occurrence of the
scarcity and conformity principles, it was not possible to perform a statistical
test.

Figure 8
Open in figure viewerPowerPoint
Absolute principle use over time
Figure 9
Open in figure viewerPowerPoint
Relative principle use over time


3.6 Q4: “WHAT IS THE SIMILARITY BETWEEN THE DIFFERENT ATTACK STEPS IN THE CRIME
SCRIPT?”

3.6.1 Q4.1: “DO PRINCIPLES DIFFER OVER THE COURSE OF AN ATTACK?”

In a multiple step attack, the average number of steps is M=1.92(SD=1.311)
therefore, the last three attack steps before compliance comprise 88% of all
attack steps. In the remaining 17 steps, there are eight single principle steps,
which all contain authority; there are four double principle steps, which all
combine authority with some other principle (i.e., commitment and reciprocity).
Furthermore, there is one triple principle step consisting of authority,
commitment, and liking, and there is one quadruple one containing authority,
conformity, commitment, and liking. Finally, there are three steps containing
another form of social influence than the six persuasion principles.

Single principle attack steps are more popular than combined principle attacks
(refer to Figure 6). Authority as a single step is used in 85.7% of the steps
immediately before compliance, 90.9% of the second steps before compliance, and
91.7% of the third steps before compliance. The use of authority (i.e., in
isolation) is relatively stable over time. The absolute use of principles over
time is shown in Figure 10, and the relative use in Figure 11.

Figure 10
Open in figure viewerPowerPoint
Absolute principle combination for each step before compliance
Figure 11
Open in figure viewerPowerPoint
Relative principle combination for each step before compliance

Despite the small numbers, in double principle attack steps the combination
authority + commitment (3 times), liking (4 times), or reciprocity (7 times) are
recurring combinations (refer to Table 4). In the final step before compliance,
67 attack steps used persuasion principles versus seven that used some other
social influence. The number of scenarios containing persuasion principles in
the last step before compliance is different from 0, χ2(1,N=74)=29.108,
p < .001.

Table 5 shows an increase of attacks using multiple principles towards the end
of the attack. Towards the moment of compliance, the relative use of single
persuasion principles in an attack step drops from 81.3% to 56.8%, whereas the
use of multiple persuasion principles in attack steps increased from 12.6% to
33.9%. This tendency is summarised in Figure 12.

Figure 12
Open in figure viewerPowerPoint
Use of principle combinations last three steps before compliance
Table 5. The number of combined principles in an attack step over time before
the target complies with the request (N=142)

Steps before compliance 1 2 3 4 5 6 Total Single 42 (56.8%) 22 (62.9%) 13
(81.3%) 3 (33.3%) 3 (60%) 2 (100%) 85 Principles Double 17 (23.0%) 5 (14.3%) 1
(6.3%) 4 (44.4%) – – 27 Triple 7 (9.5%) 2 (5.7%) 1 (6.3%) 1 (11.1%) – – 11
Quadruple 1 (1.4%) – – – 1 (20%) – 2 Other 7 (9.5%) 6 (17.1%) 1 (6.3%) 1 (11.1%)
2 (40%) – 17 Total 74 (100%) 35 (100%) 16 (100%) 9 (100%) 6 (100%) 2 (100%) 142



3.6.2 Q4.2: COMPARISON BETWEEN TWO CONSECUTIVE STEPS

In total, there are 68 consecutive attack steps identified in the 74 scenarios.
The number of principles in the former attack step does not differ from that of
its latter step, (p=.768).

There are 45 attack steps that contain persuasion principles; 39 (57.4%) attack
steps began with authority, 26 (38.2%) steps succeeded with a single authority
attack step whereas 10 (14.7%) of them consist of a combination of
authority + commitment, reciprocity, or liking. Only three consecutive steps end
with something other than authority. Finally, there are 13 steps that either
start or end with a social influence other than a persuasion principle.

The combined principles in an attack step were further decomposed. One hundred
fifteen consecutive individual principles were found in the 74 scenarios. There
are 17 steps which either begin or end (i.e., succeed) with a social influence
other than the six persuasion principles. The principles used in the former step
do not differ with respect to those in the latter step (p=.630). Out of the
remaining 99 consecutive persuasion principles, 74 (74.7%) consecutive
principles begin with authority, whereas 49 (49.5%) of the consecutive
principles also end with this principle. Furthermore, there are only 7 (7.07%)
consecutive persuasion principles, which do not involve authority.

3.6.3 Q4.3: RELATION FIRST AND LAST STEP BEFORE COMPLIANCE

There are 26 scenarios with more than one attack step. The number of persuasion
principles in the first step does not differ from those in the final step,
(p=.515).

The combined principles in an attack step were further decomposed. In total,
there are 55 scenarios with individual persuasion principles. The number of
persuasion principles used in the first attack step does not differ from those
in the final step, (p=.797). There are 37 (66%) scenarios starting with
authority, and it is used 24 times (42.9%) as the last step in the scenario.
Only six (10.7%) scenarios do not involve this principle as either the first or
last principle.


4 DISCUSSION

In social engineering attacks, offenders use persuasion principles to change the
odds of their target complying with their request. This study investigated how
persuasion principles were used in successful social engineering attacks based
on the accounts of social engineers.

The dissection of crime scripts shows that the anatomy of social engineering
attacks consists of (a) persuasion principles (refer to Q2), (b) other social
influences (refer to Q2), (c) deception, (d) real-time communication, and (e)
telephone operation (refer to Q1). The heart of the social engineering attacks
is shown in orange in Figure 13. This visualization contains the key elements of
a social engineering attack because (a) approximately 80% of the crime scripts
consist of one or two attack steps (refer to Figure 7); (b) approximately 80% of
the attack steps consist of one or two persuasion principles (refer to Figure 6
and Table 5); (c) the most frequently used persuasion principles are authority
and liking (refer to Figure 5); (d) besides persuasion principles, other social
influences are used (refer to Q2); and (e) combined persuasion principles in
attack steps always contain authority.

Figure 13
Open in figure viewerPowerPoint
Tree structure of social engineering scenarios. The time flows from right
(initial contact) to left (achieve goal). The frequency of occurrence is
specified inside the brackets. The orange coloured nodes resemble the heart of
social engineering attacks

This study gives a unique insight into how offenders use social engineering
successfully to perform their criminal act. In 88% of the attack steps,
persuasion principles were used by the offender. Hence, in 12% of the attack
steps, another social influence was used. We can therefore conclude that (based
on their accounts) social engineers make frequent use of persuasion principles
as social influences to make their targets comply with their request. Some
principles are used more frequently than others. Given the similarity between
the ranking of principles based on the success rates in the meta-analyses (refer
to Table 1) and the ranking of principles in this study (refer to Figure 5), we
believe that the occurrence of principles reflects their effectiveness in social
engineering.

In order to draw conclusions about effectiveness, an experiment would need to be
performed to verify the present conjectures. The experimental conditions can be
controlled in an experiment (i.e., the use of the persuasion principles).
Furthermore, the effectiveness can be determined because the number of subjects
who comply and do not comply is known. When the experimental design and context
are kept constant, the effectiveness of the persuasion principles can be
calculated. Such an experiment could, for example, involve a so-called technical
support scam. This involves a telephone fraud scam where the offender
impersonates technical support service personnel (Arthur, 2010). The modus
operandi often includes the offender informing the target that there is a
problem with their PC. To resolve the problem, the caller recommends buying a
small software tool to prevent further damage. The use of individual or multiple
persuasion principles can be included in the telephone script used by the
offender. One instance of this experimental design is shown in (Bullée, Montoya,
Junger, & Hartel 2016).

It was found that there are significantly more social engineering attacks
executed via the telephone, compared to other modalities. We believe that this
is because of the lower effort and risk that such an attack entails compared to
one that involves being physically present. Physically going to meet the target
implies additional risks: (a) the risk of being caught at the scene, (b) body
language could hamper the plan, and (c) the attacker can only attack once as his
face might have been recognized.

The outcome of an attack can be influenced if offenders are able to apply
persuasion principles. Literature suggests that all principles can be effective.
However, the success of principles depends on the context, operationalisation
and final goal. Milgram (1965) showed that there was a significantly lower
effect of authority when switching to the telephone modality. However, a “nurse
experiment” showed a high rate of compliance when authority was applied over the
telephone (Hofling, Brotzman, Dalrymple, Graves, & Pierce, 1966). This study
shows that authority was the most frequently successful used principle. The
reason it is most commonly executed over the telephone probably relates to its
relative low effort. Regarding authority, there are several factors that explain
its effectiveness. One of the preconditions for authority is the institutional
framework of modern society because childhood people are taught how to operate
within an institutional system. This framework is initially in the form of
regulated parental-adult authority, later through the authority of teachers in
school and finally through a boss in a company or commander in the army
(Milgram, 1963). Another precondition for authority is rewards for compliance to
authority, whereas failure to comply results in a punishment. Authority (from a
psychological point of view) is when a person is perceived to be in the position
of social control for a particular situation (Milgram, 1963). The person
claiming to be the authority will succeed if (a) someone expects an authority,
(b) appropriate dress or equipment is used (e.g., lab coat, tag, and uniform),
(c) there is absence of competing authority, and (d) there is absence of
conspicuous factors (e.g., a 5-year-old child claiming to be a pilot). Unless
contradictions in the information or anomalies appear, the authority will likely
suffice. People respond to the appearance of authority, rather than the actual
authority (Milgram, 1963). Another finding of this study is that only very few
social engineering attacks begin or end with the scarcity principle; we assume
that this reflects low success rates. Scarcity seems easy to operationalise,
because this is a frequently used technique in sales and television
advertisements (e.g., “only 25 products left” or “order today and get a 50%
discount on the second item”). Furthermore, it seems that single step attacks
only containing commitment, scarcity, or conformity are rare. The data shows
that instead, Commitment and reciprocity are used in combination with authority.
This could indicate that this combination of principles strengthens each other.

Knowledge about the principles, principle combinations and the time line in
social engineering attacks is useful for designing countermeasures. The topic of
countermeasures is discussed later in this section.

The use of a single principle occurs in almost 60% of the attack steps. The use
of combined persuasion principles is used in less than 30% of the attack steps.
This suggests that it is easier to operationalize an attack step consisting of a
single principle compared to multiple principles. Although it is likely that by
combining multiple principles in one step the effectiveness of that step
increases, the operational complexity could outweigh its benefits. To the best
of our knowledge, the issue of principle combination had not been discussed in
the literature until now.

The results of this study show that the average number of attack steps
(interactions) is two. This means that the crime script is short and that in
order to make a target comply, only information/support from one other employee
is needed. In the final step before compliance, the number of combined
principles increases. This could indicate that to make the target comply, a
boost is needed in the final attack step and that this is being achieved by
combining principles in one attack step.

The results show no difference between the number of principles used in the
first compared to the last attack step. Furthermore, there is no statistical
difference in use of principles between the former and latter of two successive
attack steps within a crime script. The results indicate that a single principle
attack step is more likely to occur after a single principle attack step.
Similarly, it is more likely that the use of authority is followed by authority.
From this, we can conclude that offenders, like all other humans, might be
creatures of habit in the sense that they stick to the method they initially
chose. We assume offenders choose their method based on successful past
attempts.

Moreover, regarding countermeasures to defeat social engineers, results showed
that successful social engineering attacks most often use authority. However,
because our society is built on the authority paradigm, it would be extremely
difficult to counteract authority by itself. We believe that it is a better
approach to use situational countermeasures. These could involve four
mechanisms; (a) procedural, (b) environmental, (c) technical, and (d)
behavioural.

Procedural countermeasures could, for example, involve the use a classification
system for all organisational data, including employee and PC names, schedules,
and software versions. Data above a certain classification threshold should not
be allowed to leave the organisation. Furthermore, in the case of someone
receiving a request, it should be determined if the request is legitimate
(Mitnick & Simon, 2002). This can be done by verifying the identity of the
requester (e.g., call-back policy or shared secret). An employee who receives a
request for information should verify the identity of the requester and initiate
the communication via a channel that is verified by the organisation. If someone
claims to be a colleague, the employment status should be confirmed (e.g.,
lookup in employee directory or contact their manager for verification). After
verifying the employment status, check the knowledge needs of that person (e.g.,
check level of classification employee or contact his manager). It is important
that the verification does not become a time-consuming process because employees
might then ignore this.

Environmental countermeasures adjust the environment to encourage a desired
behaviour. Research results show that social engineers are likely to operate via
the telephone. One environmental countermeasure could involve placing stickers
on telephones, to remind the user each time they use the telephone.

A technical solution could include using white and black lists. Telephone calls
from numbers on the white list are connected, whereas those on the black list
get terminated.

Behavioural countermeasures relate to adjusting the human: (a) by making
employees aware that there are social engineers that use social influences to
make people comply with their requests and they should realise that they are
vulnerable (Muscanell, Guadagno, & Murphy, 2014), (b) by training people to spot
a social engineering attack, (c) by making employees aware of why this is
dangerous and what the implications are for the individual and the organisation,
and (d) by distributing guidelines about what to do or not to if they are under
a social engineering attack.

Muscanell et al. (2014) describe the best practices to resist social influences
(i.e., persuasion principles). Best practices result in six questions to
counteract the individual persuasion principles: (a) Authority: When approached
by an authority, “Is this person truly whom he claims to be?” (b) Conformity:
The fact that many others do something does not guarantee that it is a correct
behaviour, hence “Would I do the same if I was alone in this situation?” (c)
Reciprocity: “Why did I get this favour? Is this an act of kindness or part of a
manipulation strategy?” (d) Commitment: Evaluate all events as independently as
possible: “Do I really want this?” (e) Liking: Separate the request from the
person: “What would I say if the request came from a different person?” (f)
Scarcity: Once something is scarce, the perceived value increases: “Is this
still an attractive offer if it wasn't scarce?”

The short-term effects of informing employees has been demonstrated by a group
of students using social engineering to obtain office keys from university
personnel. Those who received an information campaign complied significantly
less frequently than those who were not informed (Bullée, Montoya, Pieters,
Junger, & Hartel, 2015). A related relevant issue would be to assess how
learning impacts compliance over time. We expect that “quick” interventions that
are repeated on a regular basis are effective. Such an effect is already shown
in the context of cardiopulmonary resuscitation (CPR) skill retention. In this
study, the subjects were given a 4-min CPR training every 1, 2, and 3 months
after the start of the study. The final result (after 6 months) was an increase
from ±20% to ±70% of the subjects performing a perfect CPR (Sutton et al. 2011).

Finally, both the implementation and the effectiveness of the procedure should
be tested. This can be achieved by trying to social engineer one's own employees
in a controlled environment. If this is done regularly, the employees will most
likely remain responsive and alert.

When conducting experiments on humans (e.g., employees) some ethical concerns
must be taken into account. The Belmont report (1979) defines three ethical
principles for the protection of humans during testing: (a) respect for persons,
(b) beneficence, and (c) justice.

“Respect for persons incorporates at least two ethical convictions: first, that
individuals should be treated as autonomous agents, and second, that persons
with diminished autonomy are entitled to protection” (Belmont Report, 1979).
Respect for persons means that people are free to participate or to decline
participation in research. Furthermore, people who are not capable of making
competent decisions by themselves should be guided by a capable guardian.
Beneficence is defined as “persons are treated in an ethical manner not only by
respecting their decisions and protecting them from harm, but also by making
efforts to secure their well-being” (Belmont Report, 1979). This means that one
should not harm the participants. Moreover, the possible benefits of
participating should be maximised, and the potential harm should be minimised.
“Who ought to receive the benefits of research and bear its burdens?” (Belmont
Report, 1979) relates to the justice principle. Both the risks and benefits of
the study should be equally distributed within the subjects.

One ethical challenge is the use of deception because it conflicts with the
“respect for persons” principle. The use of deception might be acceptable if (a)
the experiment does not involve more than minimum risk (i.e., harm or discomfort
should not be greater than those experienced in daily life; Code of Federal
Regulations, 2005), (b) the study could not be performed without deception
(subjects in laboratory studies may behave differently than they normally would
or their behaviour may be altered because of the experimental setting), (c) the
knowledge obtained from the study has important value, and (d) when appropriate,
the subjects are provided with relevant information about the assessment
afterwards (i.e., debriefing) (Finn & Jakobsson, 2007).

Dimkov, Pieters, and Hartel (2009) described the 5 R∗ requirements in
penetration testing research (which often uses social engineering): (a)
realistic (the test should resemble a real-life scenario), (b) respectful (the
test should be done ethically) (c) reliable (the test should not cause
productivity loss of employees) (d) repeatable (repeating the test should result
in similar results), and (e) reportable (all actions should be logged). Dimkov
et al. (2009) identified conflicting requirements and noted that designing a
penetration test involves finding a balance in the requirements. For a
discussion of the three major ethics standpoints (i.e., [a] virtue ethics, [b]
utilitarianism, and [c] deontology) refer to Mouton, Malan, Kimppa, and Venter
(2015). Finally, it should be noted that in this study, the authors did not have
any control regarding the ethical concerns in the scenarios as they are
literature based.


4.1 LIMITATIONS

The proposed study has four limitations: (a) Some of the scenarios by Kevin
Mitnick that were used in the analysis might have been fictionalised to some
extent. (b) The data set contained a limited number of observations. (c) The
dataset could suffer from selection bias. It is possible that the authors could
have favoured one scenario over another one. (d) The analysis in this research
only contains success stories. This therefore provides a partial view and
influences the conclusions that can be drawn. On the other hand, available data
is limited and this analysis gives a unique insight into how offenders perform
their offences.

Finally, we summarise these recommendations for future research. The details of
all recommendations are already presented in Section 4; therefore, only a brief
summary is presented in this section. First, the analysis of the four books
shows that social engineering works. However, all scenarios in the books
involved success stories; therefore, it is unclear what the success rate of a
social engineering attack is. Experiments should be used to find the success
rates. Second, one should investigate how persuasion principles influence each
other when combined in an attack step to identify which ones have the likelihood
of succeeding. Furthermore, a useful follow-up study could involve investigating
if these social engineering attacks can be blocked or their effects reduced.
Finally, it is possible that compliance depends on cultural aspects. The
deployment of social engineering experiments in different countries could allow
to identify cross-country differences.


ACKNOWLEDGMENTS

The research leading to these results has received funding from the European
Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no.
318003 (TREsPASS). This publication reflects only the author's views and the
Union is not liable for any use that may be made of the information contained
herein. In addition, we would also like to thank Jessica Heijmans for her
valuable contribution to this research.

REFERENCES

 * Arthur, C. (2010). Virus phone scam being run from call centres in India.
   (Newspaper Article).
   http://www.theguardian.com/world/2010/jul/18/phone-scam-india-call-cent&res.
 * Asch, S. E. (1951). Effects of group pressure upon the modification and
   distortion of judgments, Groups, Leadership, and Men ( 177–190). Oxford, UK:
   Carnegie Press .
 * Assange, J. (2011). Julian Assange: The unauthorised autobiography.
   Edinburgh: Canongate Books.
 * Beauregard, E., Proulx, J., Rossmo, K., Leclerc, B., & Allaire, J-F (2007).
   Script analysis of the hunting process of serial sex offenders. Criminal
   Justice and Behavior, 34(8), 1069–1084.
 * Beauregard, E., Rebocho, M. F., & Rossmo, D. K. (2010). Target selection
   patterns in rape. Journal of Investigative Psychology and Offender Profiling,
   7(2), 137–152.
 * Belmont Report (1979). The belmont report : Ethical principles and guidelines
   for the protection of human subjects of research.
 * Blass, T. (1999). The Milgram paradigm after 35 years: Some things we now
   know about obedience to authority1. Journal of Applied Social Psychology,
   29(5), 955–978.
 * Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of
   studies using Asch's (1952b, 1956) line judgment task. Psychological
   Bulletin, 119(1), 111.
 * Bosworth, S., Kabay, M., & Whyne, E. (2014). Computer security handbook (6th
   ed.). New York: Wiley.
 * Bullée, J. H., Montoya, L., Junger, M., & Hartel, P. H. (2016).
   Telephone-based social engineering attacks: An experiment testing the success
   and time decay of an intervention. In A. Mathur, & A. Roychoudhury (Eds.),
   Proceedings of the Inaugural Singapore Cyber Security R&D Conference (SG-CRC
   2016), Singapore, Singapore, Cryptology and Information Security Series,
   Vol.  14. Amsterdam: IOS Press, pp. 107–114.
 * Bullée, J. H., Montoya, L., Pieters, W., Junger, M., & Hartel, P. H. (2015).
   The persuasion and security awareness experiment: Reducing the success of
   social engineering attacks. Journal of Experimental Criminology, 11(1),
   97–115.
 * Chan, M., Woon, I., & Kankanhalli, A. (2005). Perceptions of information
   security at the workplace: Linking information security climate to compliant
   behavior.
 * Chikudate, N. (2009). If human errors are assumed as crimes in a safety
   culture: A lifeworld analysis of a rail crash. Human Relations, 62(9),
   1267–1287.
 * Chiu, Y-N, Leclerc, B., & Townsley, M. (2011). Crime script analysis of drug
   manufacturing in clandestine laboratories: Implications for prevention.
   British Journal of Criminology, 51(2), 355–374.
 * Cialdini, R. (2009). Influence. New York:: HarperCollins.
 * Cialdini, R., Vincent, J. E., Lewis, S. K., Catalan, J., Wheeler, D., &
   Darby, B. L. (1975). Reciprocal concessions procedure for inducing
   compliance: The door-in-the-face technique. Journal of Personality and Social
   Psychology, 31(2), 206–215.
 * Code of Federal Regulations (2005). Title 45: Public Welfare, Department of
   Health and Human Services, Part 46: Protection of Human Subjects.
 * Collins, N. L., & Miller, L. C. (1994). Self-disclosure and liking: A
   meta-analytic review.Psychological Bulletin, 116(3), 457–475.
 * Cornish, D. (1994). The procedural analysis of offending and its relevance
   for situational prevention. Crime Prevention Studies, 3, 151–196.
 * Dang, H. (2008). The Origins of Social Engineering. McAffee Security Journal,
   1(1), 4–8.
 * Dimkov, T., Pieters, W., & Hartel, P. H. (2009). Two methodologies for
   physical penetration testing using social engineering. (No. TR-CTIT-09-48).
   Enschede.
 * Dreyfus, S., & Assange, J. (2012). Underground: Tales of hacking, madness and
   obsession on the electronic frontier. Edinburgh: Canongate Books.
 * Edmondson, A. C. (1996). Learning from mistakes is easier said than done:
   Group and organizational influences on the detection and correction of human
   error. The Journal of Applied Behavioral Science, 32(1), 5–28.
 * Feeley, T. H., Anker, A. E., & Aloe, A. M. (2012). The door-in-the-face
   persuasive message strategy: A meta-analysis of the first 35 years.
   Communication Monographs, 79(3), 316–343.
 * Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using r.
   London: SAGE Publications.
 * Finn, P., & Jakobsson, M. (2007). Designing ethical phishing experiments.
   IEEE Technology and Society Magazine, 26(1), 46–58.
 * Freedman, J. L., & Fraser, S. C. (1966). Compliance without pressure: The
   foot-in-the-door technique. Journal of Personality and Social Psychology,
   4(2), 195–202.
 * Gigerenzer, G. (1991). How to make cognitive illusions disappear: Beyond
   heuristics and biases. European Review of Social Psychology, 2(1), 83–115.
 * Greenspan, S. (2008). Annals of gullibility: Why we get duped and how to
   avoid it, Non-Series. Westport: Praeger.
 * Griskevicius, V., Goldstein, N. J., Mortensen, C. R., Sundie, J. M.,
   Cialdini, R. B., & Kenrick, D. T. (2009). Fear and loving in Las Vegas:
   Evolution, emotion, and persuasion. Journal of Marketing Research (JMR),
   46(3), 384–395.
 * Gupta, M., Agrawal, S. (2011). A Survey on Social Engineering and the Art of
   Deception. International Journal of Innovations in Engineering and
   Technology, 1(1), 31–35.
 * Hadnagy, C., & Wilson, P. (2010). Social engineering: The art of human
   hacking. New York:Wiley.
 * Hofling, C., Brotzman, E., Dalrymple, S., Graves, N., & Pierce, C. (1966). An
   experimental study in nurse-physician relationships. The Journal of nervous
   and mental disease, 143(2), 171.
 * Huber, M., Kowalski, S., Nohlberg, M., & Tjoa, S. (2009). Towards automating
   social engineering using social networking sites, Computational Science and
   Engineering, 2009. CSE '09. International Conference on, Vancouver, BC,
   Canada, Vol.  3, pp. 117–124.
 * Janczewski, L., & Colarik, A. (2008). Cyber warfare and cyber terrorism, Gale
   virtual reference library: Information Science Reference, Hershey, PA.
 * Kennedy, D. (2011). There's something “human” to social engineering.
   http://magazine.thehackernews.com/article-.html.
 * Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement
   for categorical data. Biometrics, 33(1) 159–174.
 * Lavorgna, A. (2014). Wildlife trafficking in the internet age. Crime Science,
   3(1), 5.
 * Luo, R. X., Brody, R., Seazzu, A., & Burd, S. (2011). Social engineering: The
   neglected human factor for information security management. Information
   Resources Management Journal, 24(3), 1–8.
 * Mann, I. (2008). Hacking the human: Social engineering techniques and
   security countermeasures. Aldershot: Gower.
 * Marconato, G. V., Kaaniche, M., & Nicomette, V. (2012). A vulnerability life
   cycle-based security modeling and evaluation approach. The Computer Journal,
   56(4), 422–439.
 * Meyerowitz, B. E., & Chaiken, S. (1987). The effect of message framing on
   breast self-examination attitudes, intentions, and behavior. Journal of
   Personality and Social Psychology, 52(3), 500–510.
 * Milgram, S. (1974). Obedience to authority: An experimental view. New
   York:Harper & Row.
 * Milgram, S. (1963). Behavioral study of obedience. The Journal of Abnormal
   and Social Psychology, 67(4), 371–378.
 * Milgram, S. (1965). Some conditions of obedience and disobedience to
   authority. Human Relations, 18(1), 57–76.
 * Mitnick, K., Simon, W. L., & Wozniak, S. (2011). Ghost in the wires: My
   adventures as the world's most wanted hacker. New York: Little, Brown.
 * Mitnick, K., & Simon, W. (2002). The art of deception: Controlling the human
   element of security. New York:Wiley.
 * Mouton, F., Malan, M. M., Kimppa, K. K., & Venter, H. (2015). Necessity for
   ethics in social engineering research. Computers & Security, 55, 114–127.
 * Muscanell, N. L., Guadagno, R. E., & Murphy, S. (2014). Weapons of influence
   misused: A social influence analysis of why people fall prey to internet
   scams. Social and Personality Psychology Compass, 8(7), 388–396.
 * O'Keefe, D. J., & Hale, S. L. (2001). An odds-ratio-based meta-analysis of
   research on the door-in-the-face influence strategy. Communication Reports,
   14(1), 31–38.
 * Pascual, A., & Guéguen, N. (2005). Foot-in-the-door and door-in-the-face: A
   comparative meta-analytic study 1. Psychological Reports, 96(1), 122–128.
 * Poulsen, K. (2011). Kingpin: How one hacker took over the billion-dollar
   Cybercrime underground. New York: Crown/Archetype.
 * Reason, J. (1990). The contribution of latent human failures to the breakdown
   of complex systems. Philosophical Transactions of the Royal Society of London
   B: Biological Sciences, 327(1241), 475–484.
 * Rhee, H.-S., Kim, C., & Ryu, Y. U. (2009). Self-efficacy in information
   security: Its influence on end users' information security practice behavior.
   Computers & Security, 28(8), 816–826.
 * Rouse, M. (2006). Definition social engineering: TechTarget.
   http://www.searchsecurity.techtarget.com/definition/social-engineering.
 * Rowe, E., Akman, T., Smith, R. G., & Tomison, A. M. (2012). Organised crime
   and public sector corruption: A crime scripts analysis of tactical
   displacement risks. Trends and Issues in Crime and Criminal Justice, 444, 1.
 * Schellevis, J. (2011). Grote amerikaanse bedrijven vatbaar voor social
   engineering.
   http://tweakers.net/nieuws/77755/grote-amerikaanse-bedrijven-vatbaar-voor-social-engineering.html.
 * Schneier, B. (2000). Secrets & lies: Digital security in a networked world
   (1st ed.). New York, NY, USA: John Wiley & Sons, Inc.
 * Sutton, R. M., Niles, D., Meaney, P. A., Aplenc, R., French, B., Abella, B.
   S., ... Nadkarni, V. (2011). Low-dose, high-frequency cpr training improves
   skill retention of in-hospital pediatric providers. Pediatrics, 128(1),
   e145–e151.
 * Szymanski, D. (2001). Modality and offering effects in sales presentations
   for a good versus a service. Journal of the Academy of Marketing Science,
   29(2), 179–189.
 * Tanford, S., & Penrod, S. (1984). Social influence model: A formal
   integration of research on majority and minority influence processes.
   Psychological Bulletin, 95(2), 189–225.
 * The Federal Bureau of Investigation (2013). Internet Social Networking Risks
   (Vol. 2013)(No. 4 October). U.S. Department of Justice. Retrieved
   23-Oktober-2013, from.
   http://www.fbi.gov/about-us/investigate/counterintelligence/internet-social-networking-risks.
 * Thompson, L., & Chainey, S. (2011). Profiling illegal waste activity: Using
   crime scripts as a data collection and analytical strategy. European Journal
   on Criminal Policy and Research, 17(3), 179–201.
 * Tremblay, P., Talon, B., & Hurley, D. (2001). Body switching and related
   adaptations in the resale of stolen vehicles. Script elaborations and
   aggregate crime learning curves. British Journal of Criminology, 41(4),
   561–579.
 * Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics
   and biases. Science, 185(4157), 1124–1131.
 * Twitchell, D. P. (2009). Social engineering and its countermeasures, Handbook
   of Research on Social and Organizational Liabilities in Information Security:
   Hershey, PA: IGI-Global, pp. 228–242.
 * USA v. Mitnick (1996). Indictment, CR 96-881, 145 F.3d 1342.
 * USA v. Mitnick (1998). No. 97-50365.
 * Whittingham, R. (2004). The blame machine: Why human error causes accidents.
   London: Taylor & Francis.
 * Winkler, I. S., & Dealy, B. (1995). Information security technology? ...
   don't rely on it: A case study in social engineering, Proceedings of the 5th
   Conference on Usenix Unix Security Symposium - Volume 5. Berkeley, CA, USA:
   USENIX Association, pp. 1–1.
 * Zhao, B., & Olivera, F. (2006). Error reporting in organizations. Academy of
   Management Review, 31(4), 1012–1030.

 * * https://www.goodreads.com/shelf/show/social-engineering
 * † http://www.scopus.com
 * ‡ The following two data assumptions must be met for chi-square analysis: (a)
   independence and (b) minimum frequency of five observations per cell (Field,
   Miles, & Field, 2012). Independence relates to putting a single observation
   in only one cell. In case one assumption is not met, the Fisher's exact test
   should be used instead.
 * § Fisher's exact test was used because the minimum number of observations was
   not met.

CITING LITERATURE



Volume15, Issue1

January 2018

Pages 20-45




 * FIGURES


 * REFERENCES


 * RELATED


 * INFORMATION


RECOMMENDED

 * Enhanced social engineering framework mitigating against social engineering
   attacks in higher education
   
   Kanos Matyokurehwa, Norman Rudhumbu, Cross Gombiro, Colletor
   Chipfumbu-Kangara, 
   SECURITY AND PRIVACY

 * Contemplating social engineering studies and attack scenarios: A review study
   
   Affan Yasin, Rubia Fatima, Lin Liu, Awaid Yasin, Jianmin Wang, 
   SECURITY AND PRIVACY

 * Social‐Engineering and Low‐Tech Attacks
   
   Karthik Raman, Susan Baumes, Kevin Beets, Carl Ness, 
   Computer Security Handbook, [1]

 * Social Engineering Attacks
   
   Hacking Multifactor Authentication, [1]

 * Weapons of Influence Misused: A Social Influence Analysis of Why People Fall
   Prey to Internet Scams
   
   Nicole L. Muscanell, Rosanna E. Guadagno, Shannon Murphy, 
   Social and Personality Psychology Compass


METRICS

Citations: 25



DETAILS

Copyright © 2017 John Wiley & Sons, Ltd.



This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs License, which permits use and distribution
in any medium, provided the original work is properly cited, the use is
non-commercial and no modifications or adaptations are made.



 * Check for updates


KEYWORDS

 * deception
 * information security
 * literature study
 * persuasion
 * social engineering


PUBLICATION HISTORY

 * Issue Online: 04 January 2018
 * Version of Record online: 14 July 2017
 * Manuscript accepted: 19 April 2017
 * Manuscript revised: 12 May 2016
 * Manuscript received: 08 October 2015




Close Figure Viewer
Return to Figure

Previous FigureNext Figure

Caption

Download PDF
back



ADDITIONAL LINKS


ABOUT WILEY ONLINE LIBRARY

 * Privacy Policy
 * Terms of Use
 * About Cookies
 * Manage Cookies
 * Accessibility
 * Wiley Research DE&I Statement and Publishing Policies
 * Developing World Access


HELP & SUPPORT

 * Contact Us
 * Training and Support
 * DMCA & Reporting Piracy


OPPORTUNITIES

 * Subscription Agents
 * Advertisers & Corporate Partners


CONNECT WITH WILEY

 * The Wiley Network
 * Wiley Press Room

Copyright © 1999-2023 John Wiley & Sons, Inc. All rights reserved


The full text of this article hosted at iucr.org is unavailable due to technical
difficulties.


LOG IN TO WILEY ONLINE LIBRARY

Email or Customer ID

Password
Forgot password?



NEW USER > INSTITUTIONAL LOGIN >


CHANGE PASSWORD

Old Password
New Password
Too Short Weak Medium Strong Very Strong Too Long


PASSWORD CHANGED SUCCESSFULLY

Your password has been changed


CREATE A NEW ACCOUNT

Email

Returning user


FORGOT YOUR PASSWORD?

Enter your email address below.

Email




Please check your email for instructions on resetting your password. If you do
not receive an email within 10 minutes, your email address may not be
registered, and you may need to create a new Wiley Online Library account.




REQUEST USERNAME

Can't sign in? Forgot your username?

Enter your email address below and we will send you your username


Email

Close

If the address matches an existing account you will receive an email with
instructions to retrieve your username

Close crossmark popup

Tweeted by 8
On 1 videos
165 readers on Mendeley
See more details