TY - GEN
T1 - A Primer on Alpha-Information Theory with Application to Leakage in Secrecy Systems
AU - Rioul, Olivier
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - 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).
AB - 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).
KW - Arimoto conditional entropy
KW - Data processing inequalities
KW - Fano’s inequality
KW - Information leakage
KW - Rényi entropy and divergence
KW - Sibson’s information
KW - Side-Channel analysis
UR - https://www.scopus.com/pages/publications/85112546374
U2 - 10.1007/978-3-030-80209-7_50
DO - 10.1007/978-3-030-80209-7_50
M3 - Conference contribution
AN - SCOPUS:85112546374
SN - 9783030802080
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 459
EP - 467
BT - Geometric Science of Information - 5th International Conference, GSI 2021, Proceedings
A2 - Nielsen, Frank
A2 - Barbaresco, Frédéric
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Geometric Science of Information, GSI 2021
Y2 - 21 July 2021 through 23 July 2021
ER -