DocumentCode
2412270
Title
A Decision Theoretic Approach to Data Leakage Prevention
Author
Marecki, Janusz ; Srivatsa, Mudhakar ; Varakantham, Pradeep
Author_Institution
IBM T.J. Watson Res., Yorktown Heights, NY, USA
fYear
2010
fDate
20-22 Aug. 2010
Firstpage
776
Lastpage
784
Abstract
In both the commercial and defense sectors a compelling need is emerging for rapid, yet secure, dissemination of information. In this paper we address the threat of information leakage that often accompanies such information flows. We focus on domains with one information source (sender) and many information sinks (recipients) where: (i) sharing is mutually beneficial for the sender and the recipients, (ii) leaking a shared information is beneficial to the recipients but undesirable to the sender, and (iii) information sharing decisions of the sender are determined using imperfect monitoring of the (un)intended information leakage by the recipients. We make two key contributions in this context: First, we formulate data leakage prevention problems as Partially Observable Markov Decision Processes; we show how to encode one sample monitoring mechanism - digital watermarking - into our model. Second, we derive optimal information sharing strategies for the sender and optimal information leakage strategies for a rational-malicious recipient as a function of the efficacy of the monitoring mechanism. We believe that our approach offers a first of a kind solution for addressing complex information sharing problems under uncertainty.
Keywords
Markov processes; decision theory; information dissemination; security of data; watermarking; data leakage prevention problems; decision theoretic approach; digital watermarking; information dissemination; information flows; information leakage; information sharing decisions; information sinks; partially observable Markov decision processes; rational-malicious recipient; Accuracy; Electronic mail; Markov processes; Monitoring; Organizations; Watermarking; data leakage prevention; digital watermarking; partially observable Markov decision process;
fLanguage
English
Publisher
ieee
Conference_Titel
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location
Minneapolis, MN
Print_ISBN
978-1-4244-8439-3
Electronic_ISBN
978-0-7695-4211-9
Type
conf
DOI
10.1109/SocialCom.2010.119
Filename
5591475
Link To Document