Detecting and characterizing social spam campaigns

  • Authors:
  • Hongyu Gao;Jun Hu;Christo Wilson;Zhichun Li;Yan Chen;Ben Y. Zhao

  • Affiliations:
  • Northwestern University, Evanston, IL, USA;HUST, Wuhan, China;U. C. Santa Barbara, Santa Barbara, CA, USA;Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;U. C. Santa Barbara, Santa Barbara, CA, USA

  • Venue:
  • Proceedings of the 17th ACM conference on Computer and communications security
  • Year:
  • 2010

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Abstract

Online social networks (OSNs) are exceptionally useful collaboration and communication tools for millions of users and their friends. Unfortunately, in the wrong hands, they are also extremely effective tools for executing spam campaigns and spreading malware. In this poster, we present an initial study to detect and quantitatively analyze the coordinated spam campaigns on online social networks in the wild. Our system detected about 200K malicious wall posts with embedded URLs, traced back to roughly 57K accounts. We find that more than 70% of all malicious wall posts are advertising phishing sites