The rapid growth of interest in quantum computing has brought about the need to secure these emerging computers against a range of security attacks. Among the potential security threats are physical attacks, including those orchestrated by malicious insiders within data centers where the quantum computers are located, which could compromise the integrity of computations and resulting data. To help in the understanding of emerging fault injection attacks on quantum computers, this paper presents an in-depth exploration of quantum computer fault injection attacks. This work introduces a classification of fault injection attacks and strategies, including an analysis of the domain of fault injection attacks, the fault targets, and the fault manifestations in quantum computers. The resulting classification highlights the landscape of the potential threats, and presents a road map for researchers and industry for developing security protection mechanisms against fault injection attacks for the emerging quantum computing systems.
The rapid growth of interest in quantum computing has brought about the need to secure these emerging computers against a range of security attacks. Among the potential security threats are physical attacks, including those orchestrated by malicious insiders within data centers where the quantum computers are located, which could compromise the integrity of computations and resulting data. To help in the understanding of emerging fault injection attacks on quantum computers, this paper presents an in-depth exploration of quantum computer fault injection attacks. This work introduces a classification of fault injection attacks and strategies, including an analysis of the domain of fault injection attacks, the fault targets, and the fault manifestations in quantum computers. The resulting classification highlights the landscape of the potential threats, and presents a road map for researchers and industry for developing security protection mechanisms against fault injection attacks for the emerging quantum computing systems.
The rapid growth of interest in quantum computing has brought about the need to secure these powerful machines against a range of physical attacks. As qubit counts increase and quantum computers achieve higher levels of fidelity, their potential to execute novel algorithms and generate sensitive intellectual property becomes more promising. However, there is a significant gap in our understanding of the vulnerabilities these computers face in terms of security and privacy attacks. Among the potential threats are physical attacks, including those orchestrated by malicious insiders within data centers where the quantum computers are located, which could compromise the integrity of computations and resulting data. This paper presents an exploration of fault-injection attacks as one class of physical attacks on quantum computers. This work first introduces a classification of fault-injection attacks and strategies, including the domain of fault-injection attacks, the fault targets, and fault manifestations in quantum computers. The resulting classification highlights the potential threats that exist. By shedding light on the vulnerabilities of quantum computers to fault-injection attacks, this work contributes to the development of robust security measures for this emerging technology.
Emergence of fault-tolerant quantum computers (FTQC) brings about promise of harnessing the power of quantum computing at larger scale. At the same time, as quantum computers are expected to process more sensitive information, there is a need to understand the security issues in fault-tolerant quantum computers, and develop defenses for attacks that may compromise confidentiality or integrity of the data processed by FTQC. While noisy intermediate-scale quantum (NISQ) computers have already been studied from the security perspective, understanding security issues with FTQC is still an open research question. To address the missing research gap, this work presents the first exploration of possible security vulnerabilities of FTQC. The work presents analysis of possible threat models and outlines potential vulnerabilities of FTQC. Understanding the landscape of the threats can help lead to development of safer FTQC design at both software and hardware levels.
Quantum computing (QC) is an emerging paradigm with the potential to transform numerous application domains by addressing classically intractable problems. However, its growing presence in cyberspace has introduced new security and privacy challenges. Similar to classical computing systems, the QC stack including software and hardware relies extensively on third parties, many of which are emerging and trust-seeking or less-trusted. This stack often contains sensitive intellectual property (IP) that demands protection. Unique features of quantum systems can enable classical-style attacks: for instance, crosstalk in multitenant settings can facilitate fault-injection attacks, while malicious calibration services can misreport error rates or miscalibrate qubits to induce denial-of-service (DoS) conditions. Given the high cost and limited availability of likely trustworthy quantum hardware, users may be enticed to explore emerging and trust-seeking but cheaper and readily available quantum hardware, which can enable the stealth of IP and tampering of quantum programs and/or computation outcomes. Similarly, emerging compilation services may compromise circuit confidentiality or insert Trojans. Despite the strategic significance of QC and its potential to process sensitive information, its security and privacy concerns remain underexplored. This article presents a comprehensive overview of QC fundamentals, key vulnerabilities, recent attack vectors, and corresponding defenses, and concludes with directions for future research to strengthen the quantum security community.
This paper introduces an extended taxonomy of faults specific to hybrid quantum-classical systems, addressing the unique challenges that arise from integrating quantum accelerators into high-performance computing (HPC) infrastructures. Building on the foundational fault classification by Avizienis et al., we incorporate fault types unique to quantum computing-such as qubit decoherence, spontaneous gate errors, and photon loss-alongside traditional and human-induced faults including development errors, operational mistakes, and malicious attacks. Our taxonomy classifies faults by their origin (natural vs. human-made), intent (accidental, deliberate non-malicious, or malicious), system boundaries (internal vs. external), and persistence (transient to permanent). We also explore how different architectural integration patterns-ranging from tight coupling to loose on-premise and cloud-based configurations-shape the manifestation and propagation of faults. These scenarios are analyzed in terms of timing mismatches, interface inconsistencies, and security threats such as data tampering and denial-of-service attacks. Through this fault-centric lens, we aim to support the co-design of dependable quantum-classical systems and highlight the critical role that integration strategies play in ensuring reproducibility, resilience, and security across hybrid computing platforms.
With the rapid advancement of artificial intelligence (AI) and quantum computing, cybersecurity threats have evolved, giving rise to adversarial quantum attacks. These attacks exploit the vulnerabilities of AI models using quantum algorithms, posing a significant risk to data security, model robustness, and decision-making systems. This paper presents a comprehensive review of adversarial quantum attacks on AI, analyzing their mechanisms, potential impacts, and countermeasures. It explores how quantum computing can enhance adversarial attacks by accelerating the generation of adversarial examples, breaking cryptographic protections, and undermining AI model integrity. Additionally, the study examines different attack vectors, including quantum-enhanced adversarial perturbations, quantum machine learning (QML) vulnerabilities, and quantum decryption threats. The paper also discusses defensive strategies such as quantum-resistant AI models, quantum cryptographic defenses, and hybrid quantum-classical security frameworks that can mitigate these risks. By evaluating existing research and emerging trends, this review provides insights into the growing intersection of AI security and quantum computing. The findings emphasize the urgent need for robust quantum-aware AI security frameworks to safeguard AI-driven systems in the quantum era. Future research directions include developing quantum-adaptive AI models, post-quantum cryptographic techniques, and real-world applications of quantum-safe AI architectures. This review aims to contribute to the ongoing discourse on ensuring AI resilience against adversarial quantum threats, paving the way for a secure and quantum-resistant future.
Quantum computing is a quantum step forward in computing technology that can transform many industries, including cybersecurity. With the development of quantum computers, they bring a lot of threats to traditional cryptographic systems, which is a concern in ensuring the security of data and communications. This paper seeks to discuss the threats of quantum computing, particularly on cryptographic systems like the RSA and elliptic curve cryptography. It also looks into measures of protection from quantum attacks, such as establishing post-quantum cryptography and hybrid encryption. Further, this paper provides a brief insight into the future of data protection with a view that organizations must prepare for this continuously advancing world. The material looks into the interaction of quantum computing and cybersecurity to enable stakeholders to develop anticipations and expectations of the future in providing secure data in a quantum world.