יובל אלוביץ

אקדמי בכיר

Analyzing group E-mail exchange to detect data leakage

Today's organizations spend a great deal of time and effort on e-mail leakage prevention. However, there are still no satisfactory solutions; addressing mistakes are not detected and in some cases correct recipients are wrongly marked as potential mistakes. In this article we present a new approach for preventing e-mail addressing mistakes in organizations. The approach is based on an analysis of e-mail exchanges among members of an organization and the identification of groups based on common topics. When a new e-mail is about to be sent, each recipient is analyzed. A recipient is approved if the e-mail's content belongs to at least one common topic to both the sender and the recipient. This can be applied even if the sender and recipient have never communicated directly before. The new approach was evaluated using the Enron e-mail data set and was compared with a well known method for the detection of e-mail addressing mistakes. The results show that the proposed approach is capable of detecting 87% of nonlegitimate recipients while incorrectly classifying only 0.5% of the legitimate recipients. These results outperform previous work, which reports a detection rate of 82% without reference to the false positive rate.

שפת פרסום אנגלית
דפים 1780-1790
כתב עת Journal of the American Society for Information Science and Technology
כרך 64
נושא מספר 9
סטטוס פרסום פורסם - 01.09.2013

Keywords

automatic classification
content analysis
e-mail

ASJC Scopus subject areas

Software
Information Systems
Human-Computer Interaction
Computer Networks and Communications
Artificial Intelligence
גישה למסמך
10.1002/asi.22886
קבצים וקישורים אחרים
Link to publication in Scopus