Victor Kebande

The paper applies Stringology-Based Cryptanalysis (SBC) using KMP and Boyer-Moore algorithms to analyze EChaCha20, confirming that the cipher maintains strong pseudorandomness and exhibits rapid diffusion, suggesting its security is robust.

The paper introduces a Neural Stringology Cryptanalysis (NSC) framework that uses machine learning to detect subtle structural patterns in stream cipher keystreams, demonstrating its potential for evaluating the robustness of ciphers like EChaCha20.

This paper proposes Stringology-Based Cryptology (SBC), a novel approach that analyzes the structural properties of cryptographic outputs by treating them as symbolic sequences, offering complementary insights to traditional statistical and algebraic cryptanalysis.

The paper introduces a stringology-based fingerprinting (SBF) framework to structurally analyze cryptographic sequences, demonstrating that pattern analysis can reveal measurable structural signatures beyond traditional statistical randomness tests.