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Reverse Social Engineering Attacks in Online Social Networks

  • Conference paper
Detection of Intrusions and Malware, and Vulnerability Assessment (DIMVA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6739))

Abstract

Social networks are some of the largest and fastest growing online services today. Facebook, for example, has been ranked as the second most visited site on the Internet, and has been reporting growth rates as high as 3% per week. One of the key features of social networks is the support they provide for finding new friends. For example, social network sites may try to automatically identify which users know each other in order to propose friendship recommendations.

Clearly, most social network sites are critical with respect to user’s security and privacy due to the large amount of information available on them, as well as their very large user base. Previous research has shown that users of online social networks tend to exhibit a higher degree of trust in friend requests and messages sent by other users. Even though the problem of unsolicited messages in social networks (i.e., spam) has already been studied in detail, to date, reverse social engineering attacks in social networks have not received any attention. In a reverse social engineering attack, the attacker does not initiate contact with the victim. Rather, the victim is tricked into contacting the attacker herself. As a result, a high degree of trust is established between the victim and the attacker as the victim is the entity that established the relationship.

In this paper, we present the first user study on reverse social engineering attacks in social networks. That is, we discuss and show how attackers, in practice, can abuse some of the friend-finding features that online social networks provide with the aim of launching reverse social engineering attacks. Our results demonstrate that reverse social engineering attacks are feasible and effective in practice.

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References

  1. Sophos Facebook ID Probe (2008), http://www.sophos.com/pressoffice/news/articles/2007/08/facebook.html

  2. Facebook Statistics (2010), http://www.facebook.com/press/info.php?statistics

  3. Sophos Security Threat 2010 (2010), http://www.sophos.com/sophos/docs/eng/papers/sophos-security-threat-report-jan-2010-wpna.pdf

  4. Balduzzi, M., Platzer, C., Holz, T., Kirda, E., Balzarotti, D., Kruegel, C.: Abusing Social Networks for Automated User Profiling. In: Jha, S., Sommer, R., Kreibich, C. (eds.) RAID 2010. LNCS, vol. 6307, pp. 422–441. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  5. Bilge, L., Strufe, T., Balzarotti, D., Kirda, E.: All Your Contacts Are Belong to Us: Automated Identity Theft Attacks on Social Networks. In: 18th International Conference on World Wide Web, WWW (2009)

    Google Scholar 

  6. Douceur, J.R.: The sybil attack. In: Druschel, P., Kaashoek, M.F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, p. 251. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  7. Flaxman, A.: Expansion and lack thereof in randomly perturbed graphs. Internet Mathematics 4(2), 131–147 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  8. Irani, D., Webb, S., Giffin, J., Pu, C.: Evolutionary study of phishing. In: eCrime Researchers Summit, pp. 1–10. IEEE, Los Alamitos (2008)

    Google Scholar 

  9. Irani, D., Webb, S., Pu, C., Li, K.: Study of Trend-Stuffing on Twitter through Text Classification. In: Collaboration, Electronic messaging, Anti-Abuse and Spam Conference, CEAS (2010)

    Google Scholar 

  10. Jagatic, T.N., Johnson, N.A., Jakobsson, M., Menczer, F.: Social phishing. Commun. ACM 50(10), 94–100 (2007)

    Article  Google Scholar 

  11. Jakobsson, M., Finn, P., Johnson, N.: Why and How to Perform Fraud Experiments. IEEE Security & Privacy 6(2), 66–68 (2008)

    Article  Google Scholar 

  12. Jakobsson, M., Ratkiewicz, J.: Designing ethical phishing experiments: a study of (ROT13) rOnl query features. In: 15th International Conference on World Wide Web, WWW (2006)

    Google Scholar 

  13. Lauinger, T., Pankakoski, V., Balzarotti, D., Kirda, E.: Honeybot, your man in the middle for automated social engineering. In: LEET 2010, 3rd USENIX Workshop on Large-Scale Exploits and Emergent Threats, San Jose (2010)

    Google Scholar 

  14. Mitnick, K., Simon, W.L., Wozniak, S.: The Art of Deception: Controlling the Human Element of Security. Wiley, Chichester (2002)

    Google Scholar 

  15. Porter, M.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)

    Article  Google Scholar 

  16. Stringhini, G., Kruegel, C., Vigna, G.: Detecting Spammers on Social Networks. In: Annual Computer Security Applications Conference, ACSAC (2010)

    Google Scholar 

  17. Webb, S., Caverlee, J., Pu, C.: Social Honeypots: Making Friends with a Spammer Near You. In: Conference on Email and Anti-Spam, CEAS (2008)

    Google Scholar 

  18. Yu, H., Kaminsky, M., Gibbons, P., Flaxman, A.: Sybilguard: defending against sybil attacks via social networks. In: Proceedings of the 2006 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, pp. 267–278. ACM, New York (2006)

    Google Scholar 

  19. Yu, H., Kaminsky, M., Gibbons, P. B., Flaxman, A.: SybilLimit: A Near-Optimal Social Network Defense against Sybil Attacks. In: IEEE Symposium on Security and Privacy (2008)

    Google Scholar 

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Irani, D., Balduzzi, M., Balzarotti, D., Kirda, E., Pu, C. (2011). Reverse Social Engineering Attacks in Online Social Networks. In: Holz, T., Bos, H. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2011. Lecture Notes in Computer Science, vol 6739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22424-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-22424-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22423-2

  • Online ISBN: 978-3-642-22424-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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