Friend or foe? Fake profile identification in online social networks

Michael Fire, Dima Kagan, Aviad Elyashar, Yuval Elovici

Research output: Contribution to journalArticlepeer-review

71 Scopus citations


The amount of personal information involuntarily exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are inundated with tens of millions of fake user profiles, which may jeopardize the user’s security and privacy. To identify fake users in such networks and to improve users’ security and privacy, we developed the Social Privacy Protector (SPP) software for Facebook. This software contains three protection layers that improve user privacy by implementing different methods to identify fake profiles. The first layer identifies a user’s friends who might pose a threat and then restricts the access these “friends” have to the user’s personal information. The second layer is an expansion of Facebook’s basic privacy settings based on different types of social network usage profiles. The third layer alerts users about the number of installed applications on their Facebook profile that has access to their private information. An initial version of the SPP software received positive media coverage, and more than 3,000 users from more than 20 countries have installed the software, out of which 527 have used the software to restrict more than 9,000 friends. In addition, we estimate that more than 100 users have accepted the software’s recommendations and removed nearly 1,800 Facebook applications from their profiles. By analyzing the unique dataset obtained by the software in combination with machine learning techniques, we developed classifiers that are able to predict Facebook profiles with a high probability of being fake and consequently threaten the user’s security and privacy. Moreover, in this study, we present statistics generated by the SPP software on both user privacy settings and the number of applications installed on Facebook profiles. These statistics alarmingly demonstrate how vulnerable Facebook users’ information is to both fake profile attacks and third-party Facebook applications.

Original languageEnglish
Article number194
Pages (from-to)1-23
Number of pages23
JournalSocial Network Analysis and Mining
Issue number1
StatePublished - 1 Jan 2014

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications


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