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Optimizing Data Misuse Detection

Optimizing Data Misuse Detection Optimizing Data Misuse Detection ASAF SHABTAI, MAYA BERCOVITCH, LIOR ROKACH, and YUVAL ELOVICI, Ben-Gurion University of the Negev Data misuse may be performed by entities such as an organization's employees and business partners who are granted access to sensitive information and misuse their privileges. We assume that users can be either trusted or untrusted. The access of untrusted parties to data objects (e.g., client and patient records) should be monitored in an attempt to detect misuse. However, monitoring data objects is resource intensive and time-consuming and may also cause disturbance or inconvenience to the involved employees. Therefore, the monitored data objects should be carefully selected. In this article, we present two optimization problems carefully designed for selecting specific data objects for monitoring, such that the detection rate is maximized and the monitoring effort is minimized. In the first optimization problem, the goal is to select data objects for monitoring that are accessed by at most c trusted agents while ensuring access to at least k monitored objects by each untrusted agent (both c and k are integer variable). As opposed to the first optimization problem, the goal of the second optimization problem is to select monitored data objects http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Knowledge Discovery from Data (TKDD) Association for Computing Machinery

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References (32)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2014 by ACM Inc.
ISSN
1556-4681
DOI
10.1145/2611520
Publisher site
See Article on Publisher Site

Abstract

Optimizing Data Misuse Detection ASAF SHABTAI, MAYA BERCOVITCH, LIOR ROKACH, and YUVAL ELOVICI, Ben-Gurion University of the Negev Data misuse may be performed by entities such as an organization's employees and business partners who are granted access to sensitive information and misuse their privileges. We assume that users can be either trusted or untrusted. The access of untrusted parties to data objects (e.g., client and patient records) should be monitored in an attempt to detect misuse. However, monitoring data objects is resource intensive and time-consuming and may also cause disturbance or inconvenience to the involved employees. Therefore, the monitored data objects should be carefully selected. In this article, we present two optimization problems carefully designed for selecting specific data objects for monitoring, such that the detection rate is maximized and the monitoring effort is minimized. In the first optimization problem, the goal is to select data objects for monitoring that are accessed by at most c trusted agents while ensuring access to at least k monitored objects by each untrusted agent (both c and k are integer variable). As opposed to the first optimization problem, the goal of the second optimization problem is to select monitored data objects

Journal

ACM Transactions on Knowledge Discovery from Data (TKDD)Association for Computing Machinery

Published: Jun 1, 2014

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