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.

Základní údaje

Originální název

Evolving boolean functions for fast and efficient randomness testing

Autoři

MRÁZEK, Vojtěch (203 Česká republika), Marek SÝS (703 Slovensko, domácí), Zdenek VASICEK (203 Česká republika), Lukáš SEKANINA (203 Česká republika) a Václav MATYÁŠ (203 Česká republika, garant, domácí)

Vydání

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

Nakladatel

Association for Computing Machinery

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Kód RIV

RIV/00216224:14330/18:00101071

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4503-5618-3

DOI

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

UT WoS

000579327800168

Klíčová slova anglicky

Boolean function; evolutionary computing; randomness; statistical test

Štítky

core_A, firank_A

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 30. 4. 2019 07:22, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

GA16-08565S, projekt VaV

Název: Rozvoj kryptoanalytických metod prostřednictvím evolučních výpočtů

Investor: Grantová agentura ČR, Advancing cryptanalytic methods through evolutionary computing

Citovat

MRÁZEK, Vojtěch, Marek SÝS, Zdenek VASICEK, Lukáš SEKANINA a 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, s. 1302-1309. ISBN 978-1-4503-5618-3. Dostupné z: 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  - JOUR
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 a 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, s.~1302-1309. ISBN~978-1-4503-5618-3. Dostupné z: https://dx.doi.org/10.1145/3205455.3205518.

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