Evolutionary computation and machine learning in cryptology
Author:
Affiliation:
1. TU Delft, The Netherlands
2. University of Zagreb, Croatia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3377929.3389886
Reference159 articles.
1. An evolutionary multiobjective approach to design highly non-linear Boolean functions
2. Efficient Template Attacks Based on Probabilistic Multi-class Support Vector Machines
3. S-box Pipelining Using Genetic Algorithms for High-Throughput AES Implementations: How Fast Can We Go?
4. On the Pitfalls of Using Arbiter-PUFs as Building Blocks
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1. Enhancing the cryptographic key using sample entropy and whale optimization algorithm;International Journal of Information Technology;2023-10-03
2. On generalizing the power function exponent constructions with genetic programming;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2022-07-09
3. Evolving constructions for balanced, highly nonlinear boolean functions;Proceedings of the Genetic and Evolutionary Computation Conference;2022-07-08
4. Evolutionary algorithms-assisted construction of cryptographic boolean functions;Proceedings of the Genetic and Evolutionary Computation Conference;2021-06-26
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