Quantum AI for Cybersecurity: A Hybrid Quantum-Classical Models for Attack Path Analysis

Modern cyberattacks are increasingly complex, posing significant challenges to classical machine learning methods, particularly when labeled data is limited and feature interactions are highly non-linear. In this study we investigates the potential of hybrid quantum-classical learning to enhance...

Security in the Era of Perceptive Networks: A Comprehensive Taxonomic Framework for Integrated Sensing and Communication Security

Integrated Sensing and Communication ISAC represents a significant shift in the 6G landscape, where wireless networks both sense the environment and communicate. While prior comprehensive surveys have established foundational elements of ISAC security, discussed perception-focused security models...

Impersonating Quantum Secrets over Classical Channels

We show that a simple eavesdropper listening in on classical communication between potentially entangled quantum parties will eventually be able to impersonate any of the parties. Furthermore, the attack is efficient if one-way puzzles do not exist. As a direct consequence, one-way puzzles are...

Post-Quantum Cryptography Key Expansion Method and Anonymous Certificate Scheme Based on NTRU

NTRU is one of the important lattice-based post-quantum cryptography methods, offering resistance against quantum computing attacks. However, a drawback of NTRU lies in its relatively low efficiency in generating key pairs. Therefore, this study proposes an NTRU-based key expansion method that...

PT-2026-26329

Protection mechanism failure in wolfCrypt post-quantum implementations ML-KEM and ML-DSA in wolfSSL on ARM Cortex-M microcontrollers allows a physical attacker to compromise key material and/or cryptographic outcomes via induced transient faults that corrupt or redirect seed/pointer values during...

Cyberscurity Threats and Defense Mechanisms in IoT Network

The rapid proliferation of Internet of Things IoT technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a comprehensive analysis of vulnerabilities, threats, and defense...

PT-2026-25314

Name of the Vulnerable Software and Affected Versions OpenSSL versions 3.5 and 3.6 OpenSSL versions prior to 3.4 OpenSSL versions prior to 3.3 OpenSSL versions prior to 3.0 OpenSSL versions prior to 1.0.2 OpenSSL versions prior to 1.1.1 Description An issue exists in OpenSSL TLS 1.3 servers where...

Quantum Machine Learning Approaches for Coordinated Stealth Attack Detection in Distributed Generation Systems

Coordinated stealth attacks are a serious cybersecurity threat to distributed generation systems because they modify control and measurement signals while remaining close to normal behavior, making them difficult to detect using standard intrusion detection methods. This study investigates quantu...

The Quantum State Continuity Problem and Temporal Enforcement against Fork Attacks

We introduce the Quantum State Continuity Problem QSCP, a security objective orthogonal to identity authentication that captures whether a systems current execution is a legitimate continuation of a unique past execution. We show that classical and stateless quantum authentication mechanisms fail...

Research Directions in Quantum Computer Cybersecurity

This document presents a concise overview of the contemporary research directions in quantum computer cybersecurity. The aim of this document is not to be a survey, but rather a succinct summary of the major research directions in quantum computer cybersecurity at the end of the first half of the...

Practical Quantum Teleportation with Finite-Energy Codebooks

Quantum communication exploits non-classical correlations to achieve efficient and unconditionally secure exchange of information. In particular, the quantum teleportation protocol allows for a deterministic and secure transfer of unknown quantum states by using pre-shared quantum entanglement an...

A Statistical Side-Channel Risk Model for Timing Variability in Lattice-Based Post-Quantum Cryptography

Timing side-channels are an important threat to cryptography that still needs to be addressed in implementations, and the advent of post-quantum cryptography raises this issue because the lattice-based schemes may produce secret-dependent timing variability with the help of complex arithmetic and...

Post-Quantum Cryptography in the 5G Core

In this work, the conventional cryptographic algorithms used in the 5G Core are replaced with post-quantum alternatives and the practical impact of this transition is evaluated. Using a simulation environment, we model the registration and deregistration of varying numbers of user equipments UEs...

Quantum-Resistant Cryptographic Models for Next-Gen Cybersecurity

Another threat is the development of large quantum computers, which have a high likelihood of breaking the high popular security protocols because it can use both Shor and Grover algorithms. In order to fix this looming threat, quantum-resistant cryptographic systems, otherwise known as...

Cyber Threat Detection Enabled by Quantum Computing

Threat detection models in cybersecurity must keep up with shifting traffic, strict feature budgets, and noisy hardware, yet even strong classical systems still miss rare or borderline attacks when the data distribution drifts. Small, near-term quantum processors are now available, but existing...

Optimizing Epsilon Security Parameters in QKD

We investigate the optimization of epsilon-security parameters in quantum key distribution QKD, aiming to improve the achievable secure key rate under a fixed overall composable security level. For this purpose, we employ a continuous genetic algorithm CGA to optimize the epsilon-security...

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

The increasing number of cyber threats and rapidly evolving tactics, as well as the high volume of data in recent years, have caused classical machine learning, rules, and signature-based defence strategies to fail, rendering them unable to keep up. An alternative, Quantum Machine Learning QML, h...

Quantum Disruption: An SOK of How Post-Quantum Attackers Reshape Blockchain Security and Performance

As quantum computing advances toward practical deployment, it threatens a wide range of classical cryptographic mechanisms, including digital signatures, key exchange protocols, public-key encryption, and certain hash-based constructions that underpin modern network infrastructures. These...

Quantigence: A Multi-Agent AI Framework for Quantum Security Research

Cryptographically Relevant Quantum Computers CRQCs pose a structural threat to the global digital economy. Algorithms like Shor's factoring and Grover's search threaten to dismantle the public-key infrastructure PKI securing sovereign communications and financial transactions. While the timeline...

FiD-QAE: A Fidelity-Driven Quantum Autoencoder for Credit Card Fraud Detection

Credit card fraud detection is a critical task in financial security, as fraudulent transactions are rare, highly imbalanced, and often resemble legitimate ones. A wide range of classical machine learning methods, as well as more recent quantum machine learning approaches, have been investigated ...