Hunting organization-targeted socialbots

Abigail Paradise, Asaf Shabtai, Rami Puzis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we perform cost-effectiveness analysis of strategies for monitoring the organizational social network in order to trap the attacker's profiles. We analyze attack strategies with different levels of knowledge on the employed monitoring strategies. The results demonstrate the efficacy in detecting the less sophisticated attackers and slowing down attackers that deliberately avoid the profiles being monitored.

Original languageAmerican English
Title of host publicationProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
EditorsJian Pei, Jie Tang, Fabrizio Silvestri
Pages537-540
Number of pages4
ISBN (Electronic)9781450338547
DOIs
StatePublished - 25 Aug 2015
EventIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France
Duration: 25 Aug 201528 Aug 2015

Publication series

NameProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Conference

ConferenceIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Country/TerritoryFrance
CityParis
Period25/08/1528/08/15

Keywords

  • Reconnaissance
  • Social network
  • Socialbots

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications

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