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 language | English |
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Pages | 765-768 |
Number of pages | 4 |
State | Published - 2011 |
Event | 18th ACM Conference on Computer and Communications Security - Chicago, United States Duration: 17 Oct 2011 → 21 Oct 2011 https://dblp.org/db/conf/ccs/ccs2011.html#GafnySRE11 |
Conference
Conference | 18th ACM Conference on Computer and Communications Security |
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Abbreviated title | 18th CCS 2011 |
Country/Territory | United States |
City | Chicago |
Period | 17/10/11 → 21/10/11 |
Internet address |