The paper investigates the ability of evolutionary computation to discover monotone Boolean functions with high nonlinearity, demonstrating that genetic programming is a highly effective encoding for…

This paper introduces a novel algorithm, CiSC, to efficiently and optimally synthesize circuit implementations of linear codes for hardware security, significantly outperforming existing state-of-the-…

This paper characterizes the graph structure, including cycle and path lengths, of Chebyshev permutation polynomials over the ring $\mathbb{Z}_{2^{k_1}3^{k_2}}$, demonstrating strong regularities desp…

This paper provides a comparative analysis and benchmarking of Secure Multi-Party Computation (SMPC) and Fully Homomorphic Encryption (FHE) for machine learning, finding that the optimal choice depend…

The paper develops a formal theory to analyze how throughput changes in AI-enhanced cybersecurity pipelines when stage capacities are perturbed by multipliers.

The paper models cryptographic hybridization as a Stackelberg game where the defender optimizes algorithm selection against a resource-constrained attacker who performs conditional optimization.

The paper introduces the base-m length codec, a canonical and robust encoding scheme that maps byte strings to lists of residues modulo m, essential for finite-ring cryptosystems.

The paper provides the first machine-checked universal proof, using ring theory, that value-independence implies identical marginal distributions for arithmetic masking, thereby extending the verifica…

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 diffu…

The paper demonstrates that cryptographically undetectable backdoors can be embedded into modern, state-of-the-art neural networks by exploiting inherent, latent geometric properties of the learned re…

This paper quantifies the polymorphic capacity of a commercial LLM, demonstrating that it can cheaply generate large populations of structurally diverse, yet behaviorally equivalent, offensive code pa…

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 eva…

The paper introduces a framework, PD-FHC, that allows users to outsource Boolean computations to an untrusted cloud while guaranteeing both computational privacy and plausible deniability against coer…

The paper argues that current lattice-based post-quantum cryptography, which relies on injecting noise, is not unconditionally secure because advanced quantum error correction and learning techniques…

The paper proposes a hybrid SAT-solving framework that uses a probabilistic-bit (p-bit) Ising sampler to guide Conflict-Driven Clause-Learning (CDCL) solvers, significantly reducing internal search ef…

This paper provides a comprehensive, system-level taxonomy for designing quantum-resistant network architectures, moving beyond simple protocol substitutions to address key distribution and management…

The paper introduces a novel public key encryption scheme with high security by leveraging the conjectured intractability of two types of highly corrupted constraint satisfaction problems (CSPs).

The paper introduces a four-stage structural dependency analysis hierarchy that enables scalable, sound first-order masking verification for large, production-level post-quantum cryptographic accelera…

The paper analyzes the security of a partially masked hardware accelerator for Number Theoretic Transform (NTT) in PQC, demonstrating that the claimed security margins are significantly overestimated…

The paper proposes constant depth threshold circuits for efficiently detecting epistasis by calculating the relative frequencies of all dataset combinations using specialized hardware architectures.