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Article
ProGuard: Detecting Malicious Accounts in Social-Network-Based Online Promotions
IEEE Access
  • Yadong Zhou
  • Dae Wook Kim, Wright State University - Main Campus
  • Junjie Zhang, Wright State University - Main Campus
  • Lili Liu
  • Huan Jin
  • Hongbo Jin
Document Type
Article
Publication Date
1-1-2017
Disciplines
Abstract

Online social networks (OSNs) gradually integrate financial capabilities by enabling the usage of real and virtual currency. They serve as new platforms to host a variety of business activities, such as online promotion events, where users can possibly get virtual currency as rewards by participating in such events. Both OSNs and business partners are significantly concerned when attackers instrument a set of accounts to collect virtual currency from these events, which make these events ineffective and result in significant financial loss. It becomes of great importance to proactively detecting these malicious accounts before the online promotion activities and subsequently decreases their priority to be rewarded. In this paper, we propose a novel system, namely ProGuard, to accomplish this objective by systematically integrating features that characterize accounts from three perspectives including their general behaviors, their recharging patterns, and the usage of their currency. We have performed extensive experiments based on data collected from the Tencent QQ, a global leading OSN with built-in financial management activities. Experimental results have demonstrated that our system can accomplish a high detection rate of 96.67% at a very low false positive rate of 0.3%.

DOI
10.1109/ACCESS.2017.2654272
Citation Information
Yadong Zhou, Dae Wook Kim, Junjie Zhang, Lili Liu, et al.. "ProGuard: Detecting Malicious Accounts in Social-Network-Based Online Promotions" IEEE Access Vol. 5 (2017) p. 1990 - 1999
Available at: http://works.bepress.com/junjie_zhang/31/