A characterisation of S-box fitness landscapes in cryptography
This addresses the challenge for cryptographers in understanding why heuristic methods struggle to design effective S-boxes, though it is incremental as it focuses on analysis rather than a new design method.
The paper tackled the difficulty of designing high-quality S-boxes in cryptography using heuristics by conducting a fitness landscape analysis, finding that almost every initial starting point leads to its own local optimum despite high network interconnectivity.
Substitution Boxes (S-boxes) are nonlinear objects often used in the design of cryptographic algorithms. The design of high quality S-boxes is an interesting problem that attracts a lot of attention. Many attempts have been made in recent years to use heuristics to design S-boxes, but the results were often far from the previously known best obtained ones. Unfortunately, most of the effort went into exploring different algorithms and fitness functions while little attention has been given to the understanding why this problem is so difficult for heuristics. In this paper, we conduct a fitness landscape analysis to better understand why this problem can be difficult. Among other, we find that almost each initial starting point has its own local optimum, even though the networks are highly interconnected.