Analyzing group communication for preventing data leakage via email

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

19 Scopus citations

Abstract

Modern business activities rely on extensive email exchange. Various solutions attempt to analyze email exchange in order to prevent emails from being sent to the wrong recipients. However there are still no satisfying solutions; many email addressing mistakes are not detected and in many cases correct recipients are wrongly marked as potential addressing mistakes. In this paper we present a new approach for preventing emails addressing mistakes in organizations. The approach is based on analysis of emails exchange among members of the organization and the identification of groups based on common topics. Each member's topics are then used during the enforcement phase for detecting potential leakage. When a new email is composed and about to be sent, each email recipient is analyzed. A recipient is approved if the email's content belongs to at least one of the topics common to the sender and the recipient. We evaluated the new approach using the Enron Email dataset. Our evaluation results suggest that the new approach easily copes with email recipients that have no previous direct connection with the sender.

Original languageEnglish
Title of host publicationProceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Pages37-41
Number of pages5
DOIs
StatePublished - 22 Sep 2011
Event2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 - Beijing, China
Duration: 10 Jul 201112 Jul 2011

Publication series

NameProceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011

Conference

Conference2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Country/TerritoryChina
CityBeijing
Period10/07/1112/07/11

Keywords

  • data leakage prevention
  • emails analysis
  • organization security

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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