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Reverse Social Engineering Attacks in Online Social Networks

  • Conference paper

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


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.


  • social engineering
  • social networks
  • privacy

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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.

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  • 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)