SocialImpact: Systematic analysis of underground social dynamics

Ziming Zhao, Gail-Joon Ahn, Hongxin Hu, Deepinder Mahi

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

8 Scopus citations

Abstract

Existing research on net-centric attacks has focused on the detection of attack events on network side and the removal of rogue programs from client side. However, such approaches largely overlook the way on how attack tools and unwanted programs are developed and distributed. Recent studies in underground economy reveal that suspicious attackers heavily utilize online social networks to form special interest groups and distribute malicious code. Consequently, examining social dynamics, as a novel way to complement existing research efforts, is imperative to systematically identify attackers and tactically cope with net-centric threats. In this paper, we seek a way to understand and analyze social dynamics relevant to net-centric attacks and propose a suite of measures called SocialImpact for systematically discovering and mining adversarial evidence. We also demonstrate the feasibility and applicability of our approach by implementing a proof-of-concept prototype Cassandra with a case study on real-world data archived from the Internet.

Original languageEnglish (US)
Title of host publicationComputer Security, ESORICS 2012 - 17th European Symposium on Research in Computer Security, Proceedings
Pages877-894
Number of pages18
DOIs
StatePublished - Sep 5 2012
Event17th European Symposium on Research in Computer Security, ESORICS 2012 - Pisa, Italy
Duration: Sep 10 2012Sep 12 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7459 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th European Symposium on Research in Computer Security, ESORICS 2012
CountryItaly
CityPisa
Period9/10/129/12/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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