TY - GEN
T1 - Evolutionary algorithms-assisted construction of cryptographic boolean functions
AU - Carlet, Claude
AU - Jakobovic, Domagoj
AU - Picek, Stjepan
PY - 2021
Y1 - 2021
N2 - In the last few decades, evolutionary algorithms were successfully applied numerous times for creating Boolean functions with good cryptographic properties. Still, the applicability of such approaches was always limited as the cryptographic community knows how to construct suitable Boolean functions with deterministic algebraic constructions. Thus, evolutionary results so far helped to increase the confidence that evolutionary techniques have a role in cryptography, but at the same time, the results themselves were seldom used. This paper considers a novel problem using evolutionary algorithms to improve Boolean functions obtained through algebraic constructions. To this end, we consider a recent generalization of Hidden Weight Boolean Function construction, and we show that evolutionary algorithms can significantly improve the cryptographic properties of the functions. Our results show that the genetic algorithm performs by far the best of all the considered algorithms and improves the nonlinearity property in all Boolean function sizes. As there are no known algebraic techniques to reach the same goal, we consider this application a step forward in accepting evolutionary algorithms as a powerful tool in the cryptography domain.
AB - In the last few decades, evolutionary algorithms were successfully applied numerous times for creating Boolean functions with good cryptographic properties. Still, the applicability of such approaches was always limited as the cryptographic community knows how to construct suitable Boolean functions with deterministic algebraic constructions. Thus, evolutionary results so far helped to increase the confidence that evolutionary techniques have a role in cryptography, but at the same time, the results themselves were seldom used. This paper considers a novel problem using evolutionary algorithms to improve Boolean functions obtained through algebraic constructions. To this end, we consider a recent generalization of Hidden Weight Boolean Function construction, and we show that evolutionary algorithms can significantly improve the cryptographic properties of the functions. Our results show that the genetic algorithm performs by far the best of all the considered algorithms and improves the nonlinearity property in all Boolean function sizes. As there are no known algebraic techniques to reach the same goal, we consider this application a step forward in accepting evolutionary algorithms as a powerful tool in the cryptography domain.
KW - Boolean function
KW - Cryptography
KW - Hidden weight boolean function
KW - Secondary construction
UR - http://www.scopus.com/inward/record.url?scp=85110054213&partnerID=8YFLogxK
U2 - 10.1145/3449639.3459362
DO - 10.1145/3449639.3459362
M3 - Conference contribution
AN - SCOPUS:85110054213
T3 - GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference
SP - 565
EP - 573
BT - GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference
PB - Association for Computing Machinery (ACM)
T2 - 2021 Genetic and Evolutionary Computation Conference, GECCO 2021
Y2 - 10 July 2021 through 14 July 2021
ER -