Poster: applying unsupervised context-based analysis for detecting unauthorized data disclosure

Authors:
Ma'ayan Gafny;Asaf Shabtai;Lior Rokach;Yuval Elovici
Affiliations:
Ben Gurion University, Beer-Sheva, Israel;Ben Gurion University, Beer-Sheva, Israel;Ben Gurion University, Beer-Sheva, Israel;Ben Gurion University, Beer-Sheva, Israel
Venue:
Proceedings of the 18th ACM conference on Computer and communications security
Year:
2011

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Abstract

In this paper, we propose a new unsupervised approach for identifying suspicious access to sensitive relational data. In the proposed method, a tree-like model encapsulates the characteristics of the result-set (i.e., data) that the user normally access within each possible context. During the detection phase, result-sets are examined against the induced model and a similarity score is derived.