Secure lossless compression

The framework of secrecy by design is introduced and the fundamental limits of lossless data compression are analyzed for this setting. The main idea behind secrecy by design is to begin with an operational secrecy constraint, which is modeled by a secrecy function fs, and then to derive fundamental limits for the performance of the resulting secrecy system. Focusing on the non-asymptotic fundamental limits of lossless compression, variable-length lossless compression and fixed-length almost-lossless compression are studied. Although it is well known that the traditional fundamental limits of variable-length and almost lossless fixed-length compression are intimately related, this relationship collapses once the secrecy constraint is incorporated. The current paper focuses on the setting in which the value of the secrecy function is known to the decompressor as side information: the main challenge is to reconcile the outcome of the information source without violating the secrecy constraint.

[1]  Yuhong Yang Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas , 2008 .

[2]  Paul W. Cuff,et al.  Rate-distortion theory for secrecy systems , 2013, 2013 IEEE International Symposium on Information Theory.

[3]  Claude E. Shannon,et al.  Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..

[4]  H. Vincent Poor,et al.  Secure lossless compression with side information , 2008, 2008 IEEE Information Theory Workshop.

[5]  A. D. Wyner,et al.  The wire-tap channel , 1975, The Bell System Technical Journal.

[6]  Elza Erkip,et al.  Source Coding under Secrecy Constraints , 2009 .

[7]  Neri Merhav,et al.  Guessing Subject to Distortion , 1998, IEEE Trans. Inf. Theory.

[8]  Sudeep Kamath,et al.  An operational measure of information leakage , 2016, 2016 Annual Conference on Information Science and Systems (CISS).

[9]  Neri Merhav Shannon's Secrecy System With Informed Receivers and its Application to Systematic Coding for Wiretapped Channels , 2007, ISIT.

[10]  Sergio Verdú,et al.  Optimal Lossless Data Compression: Non-Asymptotics and Asymptotics , 2014, IEEE Transactions on Information Theory.

[11]  E. Arıkan An inequality on guessing and its application to sequential decoding , 1995, Proceedings of 1995 IEEE International Symposium on Information Theory.

[12]  J. Massey Guessing and entropy , 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

[13]  Sudeep Kamath,et al.  Maximal leakage minimization for the Shannon cipher system , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[14]  Aaron B. Wagner,et al.  Measuring secrecy by the probability of a successful guess , 2015, Allerton.

[15]  Hirosuke Yamamoto A rate-distortion problem for a communication system with a secondary decoder to be hindered , 1988, IEEE Trans. Inf. Theory.

[16]  Paul W. Cuff,et al.  The Henchman problem: Measuring secrecy by the minimum distortion in a list , 2014, ISIT.