NDLI: An information theoretic measure for secrecy loss in stochastic discrete event systems

Content Provider	IEEE Xplore Digital Library
Author	Ibrahim, M. Jun Chen Kumar, R.
Copyright Year	2015
Description	Author affiliation: Dept. of Elec. & Comp. Eng., Iowa State Univ., Ames, IA, USA (Ibrahim, M.; Jun Chen; Kumar, R.)
Abstract	While cryptography is used to protect the content of secret information (message) by making it undecipherable, behaviors (as opposed to information) may not be encrypted, and may only be protected by partially or fully hiding through creation of ambiguity by providing covers that generate indistinguishable observations from secrets. Having a cover together with partial observability does cause ambiguity about the system behaviors to be kept secret, yet some information about secrets may still be leaked due to statistical difference between the occurrence probabilities of the secrets and their covers. One possible quantification of statistical difference between two distributions is based on their Jenson-Shannon divergence (JSD). We propose a computation of JSD for systems modeled as partially-observed Markov chains (POMC). Since an adversary is likely to discriminate more if he/she observes for a longer period, our goal is to evaluate the worst-case loss of secrecy as obtained in limit over longer and longer observations. Illustrative example is provided to demonstrate the proposed computation approach.
Starting Page	1
Ending Page	6
File Size	613346
Page Count	6
File Format	PDF
ISBN	9781467366465
e-ISBN	9781467366472
DOI	10.1109/ECAI.2015.7301204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-25
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jenson-Shannon divergence (JSD) Secrecy quantification Partially-observed Markov chains (POMC) Computational modeling Automata Observers Markov processes Steady-state Yttrium
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Change Detection in High-Resolution SAR Images Based on Jensen–Shannon Divergence and Hierarchical Markov Model

Rethinking the initialization bias problem in steady-state discrete event simulation

Stochastic Petri net representation of discrete event simulations

Discrete Time Markov Chains Competing over Resources: Product Form Steady-State Distribution

Structured risk-sensitivity for partially observed Markov chains

Bayesian Parameter Inference for Partially Observed Stochastic Volterra Equations

On optimal importance sampling for discrete-time Markov chains

Language-measure-theoretic optimal control of probabilistic finite-state systems

Designing a stochastic parameter reasoner

An information theoretic measure for secrecy loss in stochastic discrete event systems

Similar Documents

Change Detection in High-Resolution SAR Images Based on Jensen–Shannon Divergence and Hierarchical Markov Model

Rethinking the initialization bias problem in steady-state discrete event simulation

Stochastic Petri net representation of discrete event simulations

Discrete Time Markov Chains Competing over Resources: Product Form Steady-State Distribution

Structured risk-sensitivity for partially observed Markov chains

Bayesian Parameter Inference for Partially Observed Stochastic Volterra Equations

On optimal importance sampling for discrete-time Markov chains

Language-measure-theoretic optimal control of probabilistic finite-state systems

Designing a stochastic parameter reasoner

An information theoretic measure for secrecy loss in stochastic discrete event systems