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Found 7 papers, 0 papers with code
Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions
By observing the range of possible changes an operator can provide, as well as relative probabilities of specific transitions in the objective space, one can use this information to design a more effective combination of genetic operators.
On the Evolution of Boomerang Uniformity in Cryptographic S-boxes
One example of such a property is called boomerang uniformity, which helps to be resilient against boomerang attacks.
Evolving Constructions for Balanced, Highly Nonlinear Boolean Functions
Finding balanced, highly nonlinear Boolean functions is a difficult problem where it is not known what nonlinearity values are possible to be reached in general.
Evolutionary Construction of Perfectly Balanced Boolean Functions
Finding Boolean functions suitable for cryptographic primitives is a complex combinatorial optimization problem, since they must satisfy several properties to resist cryptanalytic attacks, and the space is very large, which grows super exponentially with the number of input variables.
Modeling Strong Physically Unclonable Functions with Metaheuristics
While there is no reason to doubt the performance of CMA-ES, the lack of comparison with different metaheuristics and results for the challenge-response pair-based attack leaves open questions if there are better-suited metaheuristics for the problem.
On the Difficulty of Evolving Permutation Codes
Combinatorial designs provide an interesting source of optimization problems.
On the Genotype Compression and Expansion for Evolutionary Algorithms in the Continuous Domain
This paper investigates the influence of genotype size on evolutionary algorithms' performance.
