Detecting and characterizing social spam campaigns

Hongyu Gao*, Jun Hu, Christo Wilson, Zhichun Li, Yan Chen, Ben Y. Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationCCS'10 - Proceedings of the 17th ACM Conference on Computer and Communications Security
Pages681-683
Number of pages3
DOIs
StatePublished - 2010
Event17th ACM Conference on Computer and Communications Security, CCS'10 - Chicago, IL, United States
Duration: Oct 4 2010Oct 8 2010

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Other

Other17th ACM Conference on Computer and Communications Security, CCS'10
CountryUnited States
CityChicago, IL
Period10/4/1010/8/10

Keywords

  • Online social networks
  • Spam
  • Spam Campaigns

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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