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…

Hawkeye is a system that allows perfect, precision-preserving reproduction of GPU-level matrix multiplication operations on a CPU, enabling efficient and trustworthy third-party auditing of machine le…

This survey provides a detailed overview of quantum adversarial machine learning, examining existing attacks, novel quantum-enhanced defense strategies, and the theoretical challenges in securing quan…

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…

The paper reviews adversarial machine learning vulnerabilities and proposes conceptual frameworks for enhancing AI robustness by integrating quantum computing techniques.

The paper reviews the vulnerability of AI to adversarial attacks and proposes conceptual frameworks for enhancing AI robustness by integrating quantum computing techniques.

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 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 proposes a hash-based commit-reveal alternative to minimize the infrastructural overhead associated with adopting large post-quantum signature schemes in blockchain transactions.

The paper estimates the quantum resources required to break 256-bit ECC cryptography and warns that fast-clock quantum computers could enable on-spend attacks on modern cryptocurrencies, necessitating…

This paper addresses the operational challenge of adopting Post-Quantum Cryptography (PQC) in complex financial TLS environments by presenting a methodology to automatically profile and normalize cryp…

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…

The paper introduces TIGER, a GPU-accelerated framework that significantly speeds up high-precision evaluation of nonlinear layers for encrypted LLM inference using TFHE.

This paper investigates the potential of real-world Processing-in-Memory (PIM) architectures, specifically using UPMEM, to accelerate cryptographic algorithms, demonstrating that distributing computat…

The study simulates various Post-Quantum Cryptography (PQC) signature standards for Australia's New Payments Platform, finding that Falcon-512 is the most viable candidate for maintaining Service Leve…

The paper introduces BSGS-Diagonal, a memory-efficient algorithm, and GPU-optimized kernels to significantly accelerate and reduce the resource overhead of encrypted face recognition using Fully Homom…

This survey provides a comprehensive review of the security challenges, threats, and mitigation strategies associated with the rapid advancement of quantum computing.

The paper proposes using deep learning to empirically test the indistinguishability of various post-quantum and hybrid cryptographic schemes, finding that no tested combination showed a significant ad…

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…