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Week 7.3 Semantic Attacks - Spear Phishing

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Privacy and Security in Online Social Media Course on NPTEL NOC-CS07 Week 7.3 Ponnurangam Kumaraguru (“PK”) Associate Professor ACM Distinguished Speaker fb/ponnurangam.kumaraguru, @ponguru
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Page 1: Week 7.3 Semantic Attacks - Spear Phishing

PrivacyandSecurityinOnlineSocialMedia

CourseonNPTELNOC-CS07Week7.3

PonnurangamKumaraguru(“PK”)AssociateProfessor

ACMDistinguishedSpeakerfb/ponnurangam.kumaraguru,@ponguru

Page 2: Week 7.3 Semantic Attacks - Spear Phishing

SemanticAttacks

� “Targetthewaywe,ashumans,assignmeaningtocontent.”

� Systemandmentalmodel

http://groups.csail.mit.edu/uid/projects/phishing/proposal.pdf

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Security attacks

Physical Semantic Syntactic

Phishing Mules Nigerian

Verification Security alertUpdate info

PaypalAmazon eBay BOA

Mortgage

Semanticattacks

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Subject: eBay: Urgent Notification From Billing Department

Features in the email

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Features in the email

We regret to inform you that you eBay account could be suspended if you don’t update your account information.

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https://signin.ebay.com/ws/eBayISAPI.dll?SignIn&sid=verify&co_partnerid=2&sidteid=0

Features in the email

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Website to collect information

http://www.kusi.org/hcr/eBay/ws23/eBayISAPI.htm

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Phishing Cost

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Types of Phishing Attacks

⚫Phishing

⚫Context-aware phishing / spear phishing

⚫Whaling

⚫Vishing

⚫Smsishing

⚫Social Phishing?

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Until now, work that we have seen?

⚫Using voters database

⚫Using Medical health database

⚫Using Pictures from FB

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Goal

⚫To see how phishing attacks can be performed by collecting personal information from social networks -How easily or effectively can phisher use this

information?

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Methodology

⚫Collected publicly available personal information using simple tools like Perl LWP library

⚫Correlated this data with IU’s address book database

⚫Launched in April 2005

⚫Age between 18 – 24

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Control Vs. Experiment

⚫Control: The email from IU email ID, but, from an unknown person

⚫Experiment: From a friend in IU

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Methodology

⚫ Blogging, social network, and other public data is harvested

⚫ Data is correlated and stored in a relational database

⚫ Heuristics are used to craft spoofed email message by Eve “as Alice” to Bob (a friend)

⚫Message is sent to Bob

⚫ Bob follows the link contained within the email message and is sent to an unchecked redirect

⚫ Bob is sent to attacker whuffo.com site

⚫ Bob is prompted for his University credentials

⚫ Bob’s credentials are verified with the University authenticator

⚫ a. Bob is successfully phishedb. Bob is not phished in this session; he could try again.

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Victims

⚫Control group high – sender email ID was IU

⚫Experimental condition consistent with other studies

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Success rate

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⚫70% authentications in first 12 hrs

⚫Takedown has to be successful

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Repeated authentications

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⚫ Subject tried multiple times

⚫ Tried again because “overload” message was shown

⚫ Lower bound of users to fall, continued to be deceived

⚫ Some tried 80 times

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Gender

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⚫18,294 Ms and 19,527 Fs

⚫Overall F more victims

⚫More successful if it came from opposite gender

⚫F to M (13%) was more effect than M to F (2%)

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⚫Younger targets more vulnerable

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⚫All majors significant difference between control and experimental

⚫Max difference in Science

⚫Technology lowest #satisfying ☺

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Reactions

⚫Anger -Unethical, inappropriate, illegal, fraudulent -Researchers fired -Psychological cost

⚫Denial -Nobody accepted that they fell for it -Admitting our vulnerability is hard

⚫Misunderstanding over spoofing emails ⚫Underestimation of publicly available

information

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Conclusions

⚫Extensive educational campaigns

⚫Browser solutions

⚫Digitally signed emails

⚫OSM provides lot more information for making the attack successful

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References

⚫http://markus-jakobsson.com/papers/jakobsson-commacm07.pdf

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References

⚫http://www.mpi-sws.org/~farshad/TwitterLinkfarming.pdf

⚫www.isical.ac.in/~acmsc/TMW2014/N_ganguly.ppt

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Thank [email protected]

precog.iiitd.edu.in fb/ponnurangam.kumaraguru


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