This study empirically benchmarks classical and quantum machine learning models for image recognition, finding that while quantum models offer superior accuracy and resource efficiency at high dimensi…

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 presents Broken Quantum, a comprehensive formal security audit that identifies 547 security vulnerabilities across 45 open-source quantum computing simulators, revealing critical flaws in me…

This paper presents a quantum attack on Module-LWE based lattice schemes like ML-KEM, demonstrating a polynomial-time quantum algorithm with a high success probability.

The paper introduces Quantum-Safe Code Auditor, a novel static analysis framework that uses LLMs and quantum-aware risk scoring to automatically detect and prioritize quantum-vulnerable cryptographic…

The paper proposes a layered, modular network architecture combining Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC) to achieve scalable, end-to-end post-quantum security in multi-h…

This paper reviews multidimensional reconciliation techniques for Continuous-Variable Quantum Key Distribution (CV-QKD), demonstrating how transforming the physical channel into a virtual binary chann…

This paper enhances a genetic algorithm approach for solving the Shortest Vector Problem (SVP) in lattices by incorporating domain-informed representation, thereby extending its applicability to modul…

This paper enhances a genetic algorithm approach for solving the Shortest Vector Problem (SVP) in both integral and module lattices by incorporating domain-informed representation and crossover.

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-…

MATRIX is a novel, robust code watermarking framework that encodes watermarks using constrained parity-check matrix equations, achieving high detection accuracy and improved robustness for code proven…

The paper proposes BaSE, a multi-armed bandit approach, to optimally allocate a fixed budget of LLM calls across parallel evolutionary search trajectories, significantly improving mean fitness and rel…

This paper presents a GPU-accelerated implementation of a Learning with Errors (LWE)-based Key Encapsulation Mechanism (KEM), demonstrating significant speedups and energy efficiency gains on modern G…

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 introduces 'quantum-safe,' a Python library that addresses the remaining 'production gap' in post-quantum cryptography (PQC) by providing robust, easy-to-use hybrid implementations and compr…

The paper introduces an operational post-quantum X.509 assurance framework that rigorously validates ML-KEM and ML-DSA certificates and keys across various deployment stages, achieving comprehensive d…

The paper identifies a universal, statistically predictable distribution (Mandelbrot) governing LLM outputs, enabling a highly efficient, model-agnostic scoring primitive for provenance and quality as…

The paper proposes a two-dimensional coordinate system to map the co-evolution of cryptographic resilience and computational capability, identifying the 'Quantum Gap' as the primary systemic risk requ…

The paper introduces Atomic Decomposition and Recombination (ADR), a novel framework that generates genuinely novel and challenging verifiable code tasks, significantly improving the scalability of Re…

The paper introduces a unified framework for Quantum Fully Homomorphic Encryption (QFHE) that achieves exponential efficiency improvements by integrating a novel modular arithmetic program (MAP) tailo…