Systems and Means of Informatics
2017, Volume 27, Issue 4, pp 144149
BANS OF PROBABILITY MEASURES IN THE PROBLEM OF INSIDER DETECTION
Abstract
A data model for a common work of a finite set of analysts is considered. Among analysts, there can be an insider who due to access to forbidden data can cause damage to the organization. Operation of each analyst is described by a random series of samples of data, admissible for him. The process of addressing the forbidden data is described by bans of probability measures defining honest operation of analysts. The method of definition of the set of bans which allows to use the theory of bans correctly is constructed. It helps to identify the insider by a finite number of observations over operations of analysts.
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[+] About this article
Title
BANS OF PROBABILITY MEASURES IN THE PROBLEM OF INSIDER DETECTION
Journal
Systems and Means of Informatics
Volume 27, Issue 4, pp 144149
Cover Date
20171030
DOI
10.14357/08696527170411
Print ISSN
08696527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
insider; information security; theory of bans of probability measures; mathematical statistics
Authors
E. A. Martyanov
Author Affiliations
Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, 152 Leninskie Gory, GSP1, Moscow 119991, Russian Federation
