Evolving boolean functions for fast and efficient randomness
testing

D 2018

Evolving boolean functions for fast and efficient randomness testing

MRÁZEK, Vojtěch; Marek SÝS; Zdenek VASICEK; Lukáš SEKANINA; Václav MATYÁŠ et. al.

Basic information

Original name

Evolving boolean functions for fast and efficient randomness testing

Authors

MRÁZEK, Vojtěch (203 Czech Republic); Marek SÝS (703 Slovakia, belonging to the institution); Zdenek VASICEK (203 Czech Republic); Lukáš SEKANINA (203 Czech Republic) and Václav MATYÁŠ (203 Czech Republic, guarantor, belonging to the institution)

Edition

USA, Proceedings of the Genetic and Evolutionary Computation Conference 2018, p. 1302-1309, 8 pp. 2018

Publisher

Association for Computing Machinery

Other information

Language

English

Type of outcome

Proceedings paper

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14330/18:00101071

Organization unit

Faculty of Informatics

ISBN

978-1-4503-5618-3

DOI

http://dx.doi.org/10.1145/3205455.3205518

UT WoS

000579327800168

EID Scopus

2-s2.0-85050582312

Keywords in English

Boolean function; evolutionary computing; randomness; statistical test

Abstract

V originále

The security of cryptographic algorithms (such as block ciphers and hash functions) is often evaluated in terms of their output randomness. This paper presents a novel method for the statistical randomness testing of cryptographic primitives, which is based on the evolutionary construction of the so-called randomness distinguisher. Each distinguisher is represented as a Boolean polynomial in the algebraic normal form. The previous approach, in which the distinguishers were developed in two phases by means of the brute-force method, is replaced with a more scalable evolutionary algorithm (EA). On seven complex datasets, this EA provided distinguishers of the same quality as the previous approach, but the execution time was in practice reduced 40 times. This approach allowed us to perform a more efficient search in the space of Boolean distinguishers and to obtain more complex high-quality distinguishers than the previous approach.

Links

GA16-08565S, research and development project

Name: Rozvoj kryptoanalytických metod prostřednictvím evolučních výpočtů

Investor: Czech Science Foundation

Cite

MRÁZEK, Vojtěch; Marek SÝS; Zdenek VASICEK; Lukáš SEKANINA and Václav MATYÁŠ. Evolving boolean functions for fast and efficient randomness testing. In Proceedings of the Genetic and Evolutionary Computation Conference 2018. USA: Association for Computing Machinery, 2018, p. 1302-1309. ISBN 978-1-4503-5618-3. Available from: https://dx.doi.org/10.1145/3205455.3205518.

@inproceedings{1423716,
   author = {Mrázek, Vojtěch and Sýs, Marek and Vasicek, Zdenek and Sekanina, Lukáš and Matyáš, Václav},
   address = {USA},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference 2018},
   doi = {http://dx.doi.org/10.1145/3205455.3205518},
   keywords = {Boolean function; evolutionary computing; randomness; statistical test},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {USA},
   isbn = {978-1-4503-5618-3},
   pages = {1302-1309},
   publisher = {Association for Computing Machinery},
   title = {Evolving boolean functions for fast and efficient randomness testing},
   url = {https://dl.acm.org/citation.cfm?id=3205518},
   year = {2018}
}

TY  - CONF
ID  - 1423716
AU  - Mrázek, Vojtěch - Sýs, Marek - Vasicek, Zdenek - Sekanina, Lukáš - Matyáš, Václav
PY  - 2018
TI  - Evolving boolean functions for fast and efficient randomness testing
PB  - Association for Computing Machinery
CY  - USA
SN  - 9781450356183
KW  - Boolean function
KW  - evolutionary computing
KW  - randomness
KW  - statistical test
UR  - https://dl.acm.org/citation.cfm?id=3205518
N2  - The security of cryptographic algorithms (such as block ciphers and hash functions) is often evaluated in terms of their output randomness. This paper presents a novel method for the statistical randomness testing of cryptographic primitives, which is based on the evolutionary construction of the so-called randomness distinguisher. Each distinguisher is represented as a Boolean polynomial in the algebraic normal form. The previous approach, in which the distinguishers were developed in two phases by means of the brute-force method, is replaced with a more scalable evolutionary algorithm (EA). On seven complex datasets, this EA provided distinguishers of the same quality as the previous approach, but the execution time was in practice reduced 40 times. This approach allowed us to perform a more efficient search in the space of Boolean distinguishers and to obtain more complex high-quality distinguishers than the previous approach.
ER  -

MRÁZEK, Vojtěch; Marek SÝS; Zdenek VASICEK; Lukáš SEKANINA and Václav MATYÁŠ. Evolving boolean functions for fast and efficient randomness testing. In \textit{Proceedings of the Genetic and Evolutionary Computation Conference 2018}. USA: Association for Computing Machinery, 2018, p.~1302-1309. ISBN~978-1-4503-5618-3. Available from: https://dx.doi.org/10.1145/3205455.3205518.

Přehled o publikaci