Applying Unsupervised Context-Based Analysis for Detecting Unauthorized Data Disclosure

Research output: Contribution to conferencePosterpeer-review

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.
Original languageEnglish GB
Pages765-768
Number of pages4
StatePublished - 2011
Event18th ACM Conference on Computer and Communications Security - Chicago, United States
Duration: 17 Oct 201121 Oct 2011
https://dblp.org/db/conf/ccs/ccs2011.html#GafnySRE11

Conference

Conference18th ACM Conference on Computer and Communications Security
Abbreviated title18th CCS 2011
Country/TerritoryUnited States
CityChicago
Period17/10/1121/10/11
Internet address

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