A Primer on Alpha-Information Theory with Application to Leakage in Secrecy Systems

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Abstract

We give an informative review of the notions of Rényi’s α -entropy and α -divergence, Arimoto’s conditional α -entropy, and Sibson’s α -information, with emphasis on the various relations between them. All these generalize Shannon’s classical information measures corresponding to α= 1. We present results on data processing inequalities and provide some new generalizations of the classical Fano’s inequality for any α> 0. This enables one to α -information as a information theoretic metric of leakage in secrecy systems. Such metric can bound the gain of an adversary in guessing some secret (any potentially random function of some sensitive dataset) from disclosed measurements, compared with the adversary’s prior belief (without access to measurements).

Original languageEnglish
Title of host publicationGeometric Science of Information - 5th International Conference, GSI 2021, Proceedings
EditorsFrank Nielsen, Frédéric Barbaresco
PublisherSpringer Science and Business Media Deutschland GmbH
Pages459-467
Number of pages9
ISBN (Print)9783030802080
DOIs
Publication statusPublished - 1 Jan 2021
Event5th International Conference on Geometric Science of Information, GSI 2021 - Paris, France
Duration: 21 Jul 202123 Jul 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12829 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Geometric Science of Information, GSI 2021
Country/TerritoryFrance
CityParis
Period21/07/2123/07/21

Keywords

  • Arimoto conditional entropy
  • Data processing inequalities
  • Fano’s inequality
  • Information leakage
  • Rényi entropy and divergence
  • Sibson’s information
  • Side-Channel analysis

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