A compression perspective on secrecy measures

Yanina Y. Shkel, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The relationship between secrecy, compression rate, and shared secret key rate is surveyed under perfect secrecy, equivocation, maximal leakage, local differential privacy, and secrecy by design. It is emphasized that the utility cost of jointly compressing and securing data is very sensitive to (a) the adopted secrecy metric and (b) the specifics of the compression setting. That is, although it is well-known that the fundamental limits of traditional lossless variable-length compression and almost-lossless fixed-length compression are intimately related, this relationship collapses for many secrecy measures. The asymptotic fundamental limit of almost-lossless fixed length compression remains entropy for all secrecy measures studied. However, the fundamental limits of lossless variable-length compression are no longer entropy under perfect secrecy, secrecy by design, and sometimes under local differential privacy. Moreover, there are significant differences in secret key/secrecy tradeoffs between lossless and almost-lossless compression under perfect secrecy, secrecy by design, maximal leakage, and local differential privacy.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages995-1000
Number of pages6
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: Jul 21 2020Jul 26 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
CountryUnited States
CityLos Angeles
Period7/21/207/26/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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