Don’t be a Phish: Steps in User Education
Stefan A. Robila
Montclair State University
RI 301, Computer Science
Montclair, NJ 07043
James W. Ragucci
Montclair State University
RI 301, Computer Science
Montclair, NJ 07043
Phishing, e-mails sent out by hackers to lure unsuspecting victims
into giving up confidential information, has been the cause of
countless security breaches and has experienced in the last year an
increase in frequency and diversity. While regular phishing
attacks are easily thwarted, designing the attack to include user
context information could potentially increase the user’s
vulnerability. To prevent this, phishing education needs to be
considered. In this paper we provide an overview of phishing
education, focusing on context aware attacks and introduce a new
strategy for educating users by combining phishing IQ tests and
class discussions. The technique encompasses displaying both
legitimate and fraudulent e-mails to users and having them
identify the phishing attempts from the authentic e-mails. Proper
implementation of this system helps teach users what to look for
in e-mails, and how to protect their confidential information from
being caught in the nets of phishers. The strategy was applied in
Introduction to Computing courses as part of the computer
security component. Class assessment indicates an increased level
of awareness and better recognition of attacks.
Categories and Subject Descriptors
K.3.2 [Computer and Education]: Computer & Information
Science Education – Computer Science Education, Curriculum.
C.2.0 [Computer-Communication Networks]: General -
Security & Protection, K.6.5 [Management of Computing &
Information Systems]: Security & Protection Education
Reliability, Experimentation, Security, Human Factors
Phishing, information security, computer education
Evolution does not only apply to plants and animals, it also
applies to human technology. Armor, for instance, was designed
to protect the wearer from being wounded. Technology eventually
evolved to find ways of piercing or breaking that armor. In
response, various types of armor have been developed to protect
the wearers from the new methods of destroying the armor,
creating an endless cycle of improvement within technology.
When one side improved its defenses, the other side would
improve its offences. Computer security and security threats have
evolved in the same manner. Throughout this ongoing race, one
thing remained constant as the weakest link, the human factor .
Spam, defined as the unsolicited sending of commercial e-mail
advertisements , which combined with online fraud has caused
losses of over 200 million dollars in 2003 alone . A defense
against the overabundance of spam is the implementation of spam
filters currently used within most of the organizations or free mail
systems. Social engineering, defined by Kevin Mitnick as “using
manipulation, influence and deception to get a person, a trusted
insider within an organization to comply with a request, and the
request is usually to release information or perform some sort of
action item that benefits that attacker” transforms spam to the
next level in the evolutionary chain. A combination of fraudulent
spam e-mail with social engineering creates a relatively new tactic
called Phishing. Phishing is using social engineering to send spam
e-mail(s) to unsuspecting victims, known as phishes . The e-
mails are disguised (“spoofed”) as coming from legitimate
corporations and aim at directing users to copies of legitimate
websites. The “phishers” goal is to “fish” for confidential
information that the phishes have access to, such as bank account
numbers, usernames, passwords and social security numbers .
Phishing attacks come in a large variety of flavors. Some attacks
may masquerade as security upgrades or information verification
from the Bank of America. In more recent times, some phishing
attacks have appeared claiming to be a charity organization
collecting money to benefit the victims of Hurricane Katrina or
the 2004 Indian Ocean Tsunami  as seen in Fig 1 . Damage
from these attacks is immense. Between May 2004 through May
2005, approximately 1.2 million U.S. computer users suffered
losses of nearly one billion dollars . The United States is not
the only target. In the United Kingdom, it was reported in March
2005 that damage jumped 20% to cause 504 million pounds in
damage . In addition, phishing attacks were also reported in
non-English speaking countries as early as 2004 .
Although the frequency of phishing attacks has recently stabilized
, context aware phishing is of particular concern for the
future. A context aware attack consists of the phisher gaining
knowledge of what sites and services the phish uses and
customizing an attack that appears to be from the target’s service
. While currently, a phishing attack success rate is under 1%
 a context aware attack would result in much higher rates .
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Faced with these prospects, one must see what tools are available
to fight phishing. On one hand, application development will
continue to improve spam and phishing detection. On the other
hand, human factor risks can be reduced by spam and phishing
education. In this paper we analyze various efforts in educating
students related to phishing and we discuss our experience with
teaching based on phishing IQ tests and context information. The
paper is organized as follows. In Section 2 we briefly look at
previous phishing education efforts. In Section 3 we discuss
context aware phishing and the design of context aware attacks
and tests. In Section 4 we discuss the pedagogical setting for
phishing education. Section 5 presents a summary of the IQ tests
as well as results of the educational assessment survey. We end
the paper with Conclusions and Future Work (Section 6) and
2. PHISHING EDUCATION
Anti-phishing action is supported by a wide group of interesting
parties including most of the financial institutions. Private and
government institutions have developed phishing awareness
websites including , , .
According to , there are five individual issues that have to be
addressed in order to combat phishing: education, preparation,
avoidance, intervention and treatment. Within these groupings,
education is given the least attention. The paper only states that
users need to be educated in how to recognize suspicious requests
in their e-mail. There is minimal instruction of how users should
learn how to identify phishing attacks. In fact, both  and 
briefly list what should be taught to users, but they do not list a
vehicle for this education. The websites listed above, while
relatively up to date, mainly provide a description of phishing
attacks and some good sense advice.
An alternative approach is described in . Researchers at
Indiana University conducted a study of 1,700 students in which
they collected websites frequently visited by students and either
sent them phishing messages or spoofed their e-mail addresses.
The respondents were provided with a discussion forum and were
informed of their participation in the study. Nevertheless, while
the authors indicate that public awareness was of concern, the
only clear outcome was an increased effort on the university IT to
protect against phishing. The large success rate of the attacks
(over 50% in some experiments) was mainly due to the use of
social context information.
One tool that has been developed by  to educate users is a
phishing IQ test. The test provides users with a combination of
actual phishing attacks and legitimate e-mails and users are asked
to distinguish between them. Once finished the user is given a
score of how well he or she was able to identify the e-mail. As a
result of this IQ test, users’ awareness of phishing increased. In a
period of a year, the test has seen an average score increase of 14
points, with this year the average score being a 75% .
Although this increase is a good sign, the average score shows
that 25% of the e-mails are wrongly identified. Results show that
82% of the test takers identify phishing e-mails correctly, but
legitimate e-mails are only identified correctly worldwide 52% of
the time . This alarmingly low number compared to the
correct number of detected phishing attempts could probably be
attributed to users classifying all of the e-mails on the test as phish
3. CONTEXT AWARE PHISHING AND
While benign in nature, the MailFrontier’s IQ tests have limited
usability in a classroom. Given its generality, it is likely that most
of the students will have never dealt with the companies listed in
the tests. As such, the corresponding messages would have end up
being classified as SPAM from the beginning, would have been
placed in a bulk folders, or deleted without being opened .
Alternatively, the Social Phishing experiments described in 
would have a stronger impact since they addressed entities
familiar to the users. However, a direct phishing attack targeting
the students, while interesting from the point of research, would
have limited educational impact.
We suggest a hybrid approach where we employ IQ tests enriched
by social contexts. Borrowing from the idea of context aware
phishing attacks, described in , if an IQ test is developed
using known services that a group of users have a high probability
of using, then the element of inexperience with the
company/service is eliminated. Instead, users would be familiar
with the source that they are being tested on and should be better
able to identify real e-mails from fraudulent phishing attempts.
Once this is accomplished, then a different set of reasons can be
assumed for a user to falsely identify an e-mail. Reasons for false
identification might include any of the following:
− User is unaware of what phishing is.
− User is aware of phishing, unaware how to search for it.
− User does not suspect a phishing attempt from that
There are several approaches that would allow collection of social
context information. These include collection of browser data
(such as history collection, auto-fill properties, etc. - for some
excellent examples, visit ), exploit of the browser tabs ,
access to user’s labs, and crawling social network websites .
Fig 1. Phishing Example
We pursued to design a customized phishing IQ test focused on
Montclair State University students. Picking companies and
online services that a large portion of the student body uses per
the specifications addressed above in section three required
different strategies of data collection. Most of the data was
collected from the computer laboratory where the test was
administered and the campus computer centers. All of the
computers examined in these locations underwent browser
analysis from tools found at  followed by analysis of the
browsers cache and local history to determine if people used the
machines to visit any additional websites of interest. Other
websites that were used for this project were included after
looking at the resources available to students on campus. For
instance, the ATM machines on the MSU campus are run by
BankX. Therefore, it is logical to assume that many, if not most of
the students who attend the university have an account at BankX
to avoid service charges when using the ATM machines. We also
note that while the use of social network websites is very
attractive, generating user personalized IQ tests was beyond the
scope of our work.
Once the data of what MSU students use was gathered, phishing
and legitimate e-mails were generated and mixed with others from
a variety of sources including  and  and then grouped in
an IQ survey that contained 12 questions, with six answers that
are legitimate and six that are phishing attacks. At the end, the
survey was formed with messages from: University registrar (P),
Ebay.com (L), BankX (L), University Parking (L), MySpace.com
(P), BankY (L), Fastweb.com (L), Amazon.com (P), Paypal.com
(P), Yahoo.com (P), Blackboard.com (P), Facebook.com (L)
where P and L indicate a phishing or a legitimate e-mail
respectively. Fig 2 shows a sample question related to
Facebook.com. To implement the survey and record the results we
Tomcat server running on a Sun Solaris box. A survey taker
would be presented with images of an email at a time and asked to
indicate if it is a phishing attempt or not. Upon selecting and
confirming an answer, the next e-mail image was displayed. At
the end, the application displayed the number of correct answers.
4. EDUCATIONAL APPROACH
Fig. 3 describes the steps taken in discussing and testing phishing
knowledge. We started by presenting what phishing is and
discussing its implications. Following, we discussed the nature of
the phishing emails and we discussed the methods that can be
employed by attackers to generate better targeted messages as well
as identify many browser and web vulnerabilities. Next, we
discussed ways to increase public awareness on phishing and
debated on aggressive (such as the phishing emails used in )
versus passive (such as the IQ tests ) education.
Steps six and seven were used to assess the quality of the
instruction. First, an IQ survey was administered followed by a
class assessment survey. The session was timed at approximately
30 minutes. A control number was presented to the survey taker.
The number could be used to show that the student has taken the
survey; however, it could not be related to the answers, in order to
4.2 Course Description
We have applied the phishing education module to two sections of
our Introduction to Computing course. Approved to satisfy the
General Education requirements for computer fluency in a liberal
arts college, the course includes one lecture and one lab session
every week for a semester. The lectures are dedicated to various
computing issues such as computer organization, structured
programming, networks, privacy and ethics, while the labs are
focused on acquiring skills on various productivity packages as
well as learning basic concepts in programming, web development
and netiquette. The course is attended by large numbers of non-
science majors and it is organized in sections of up to 24 students
(due to lab space limitations).
As per the arguments in , the Introduction to Computing
course was a natural choice for piloting the phishing education
module since the vast majority of students will have computing
experience mainly from the user’s point of view. In addition, one
component of the course is teaching students about basic
computer and network security issues, a broad topic that includes
phishing. Finally, the lab component of the course allowed us to
have the students take the surveys in a set timeframe and to
discuss the general results immediately.
Of the 48 IQ surveys completed, we recorded an average
correctness rate of approximately 6.87 corresponding to an
Fig 2. Phishing e-mail created from a confirmation e-mail
sent by Facebook.com to a dummy account
Fig. 3 Phishing Education Steps
1. Learn what phishing is 
2. Understand the implications of phishing 
3. Discuss the ways phishing can be detected , 
4. Discuss the ways phishing information can be collected.
5. Discuss ways to evaluate phishing education , 
6. Fill Phishing IQ
7. Discuss general results and evaluate the session.
average IQ of 57.29%. This means that approximately one out of
two e-mails, the students would erroneously identify a legitimate
message as a phishing attack, or a phishing attack, as a legitimate
Next, we analyzed the success rate for the legitimate and phishing
e-mails respectively. In case of the legitimate e-mails, the students
we able to correctly identify on average 3.64 out of 6 (60%) while
the phishing e-mails were recognized on average 3.22 out of 6
(53%). Interestingly, the messages easiest recognized as legitimate
was one from Fastweb.com (81% correct match rate) while the
lowest legitimate recognition was received by a message from
BankX (50% correct match rate). For phishing, the lowest correct
identification was achieved by a message purporting to be from
the university’s registrar office (35% correct match rate) while the
highest was built from scratch claiming to be from an instructor
and referring students to Blackboard.com (75%). We note that the
question with the lowest overall correct match rate, the phishing
attempt based on the university’s registrar’s office, was requesting
the student to login and verify personal information. At the time
of the survey administration, the university was revealing that a
large number of student data was inadvertently disclosed publicly
and that identity theft risk for the students was increased. We
believe that the students were aware of the incident and that this
played a major role in their choice for an answer. If such a
phishing attack would have really occurred, a 65% success rate
would have been disastrous. Also note that a month after the
survey was administered, the university sent a legitimate version
of the e-mail to the student body.
A second survey was administered to students to evaluate the
educational value of the session. The surveys were anonymous
and no points were awarded based on its completion. 78% of the
respondents indicated that they were not aware of phishing prior
to the class. At the same time, 93% acknowledged receiving
possible phishing e-mails in the past and 28% revealed that they
probably answered to phishing attacks in the past.
Fig. 4 and 5 are examples of the questions intended to test
understanding of social context factors for phishing. We note that,
as previously reported, most of the students still consider
messages from a friend as legitimate, although a large minority
(40%) now has second thoughts. In addition, most of the
participating students have become aware of the vulnerabilities
existing in browser data (see Fig 5). The students have positively
perceived both the IQ surveys as well as the overall phishing
session, with 94% agreeing that the IQ survey was helpful (Fig 6)
and all agreeing that the session was helpful (Fig. 7).
Finally, class discussions have revealed that most of the students
place significant trust in the educational institutions as well as the
social network websites. As such, while many have easily
declared that they would ignore banking or auction/payment site
emails, they were surprised to discover that attacks could occur by
spoofing the university or social network website communication.
We believe that this is explainable by the current focus of the anti-
phishing and anti ID-theft campaigns that put emphasis on
protection of financial and health information and ignore popular
web destinations. Unfortunately, such destinations also handle
private information (such as names, addresses, date of birth)
which can be used for identity theft. Successful phishing attacks
based on them would be equally disastrous.
Fig 4. Receiving a message from a friend makes me less likely
to assume it is a phishing attempt.
Fig. 5 Information stored by the Internet browser can be used
to refine a phishing attack.
Fig. 6 The phishing IQ survey was helpful in understanding
Fig. 7 Attending this session made me more informed about
phishing and less likely to fall prey to such an attack.
Phishing has become a significant problem for internet users.
While most of its effects are noticeable in the United States, it is
expected that phishing will continue to expand all over the world.
Recent reports such the ones produced by the Antipishing
Working Group  and the Korea Internet Security Center 
reflect these trends and predict a continuous increase in attacks
and diversity. While technology advances continue to fight the
problem, user education continues to constitute a significant
In this paper we have discussed an approach to user education that
involves quantitative testing and social context aware examples.
The strategy allowed us to include phishing topics in an
Introduction to Computing course aimed at students pursuing a
non-computer science education. The phishing IQ test and the
session evaluation survey reveal that the current student body is
mostly oblivious to phishing threats. Upon being exposed to the
topics and shown how to analyze a message for phishing
characteristics, students are able to correctly identify most of the
threats. The students have positively appreciated the session and
its format and have acknowledged its usefulness.
More work remains to be done. Given a predicted increase in
tools available to fight phishing, it is expected that future attacks
will continue to be more and more refined in user and event
specificity. Previous work together with our experiments show
that such attacks have an extremely high success rate since they
most likely appeal to the user’s emotions. Accordingly, phishing
education will continue to be improved by use of user specific
tools. A social aware IQ test, that would be personalized on each
user, could be such a tool.
Our work can be expanded for use in other courses as well for
general public training. Coupled with context information, one
can always design specific tests, targeted at specific user groups.
Overall, our approach to phishing education was shown to be an
We would like to thank Dr. Carl Bredlau for his vital part in the
construction of the creation of the survey using jsp files, as well as
hosting the files on his server.
A sample of the phishing test together with other materials is
available at http://www.csam.montclair.edu/~robila/RSL/Phish/
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