ABSTRACT The intersection of quantum computing and voice technology offers unparalleled security challenges and opportunities. In this paper, we propose quantum voice security as an interdisciplinary research field, bridging vulnerabilities where quantum algorithms breach classical voice protection mechanisms while enabling new defense mechanisms. We define a mathematical model for quantum based threats: (1) As cryptographic collapse by Shor's algorithm, breaching RSA/ECC (elliptic‐curve cryptography) protected voice biometrics and communications in polynomial time, enabling store now, decrypt later (SNDL) attacks; (2) As in adversarial amplification by Grover optimized perturbations in Fock space using entanglement monogamy for cross‐model transferability; (3) In biometric spoofing , by relativistic Quantum Generative Adversarial Networks (RQGANs), producing voiceprints indistinguishable from validated data under trace distance (TD) metrics. Concurrently, we define post‐quantum mitigation solutions: (i) In lattice based cryptosystems , (RLWE (Ring Learning With Errors) with ‐bit strength) safeguarding voiceprint encryption against quantum decoherence; (ii) in quantum based detection , by Wigner function negativity () and holographic entropy bound violation () to identify deepfakes; (iii) In hybrid authentication protocols (e.g., entanglement‐swapped TLS‐QUIC (Transport Layer Security over QUIC)) with composable security . Experimental results on multiple audio datasets ( LibriSpeech , Brahms ) validate quantum vulnerabilities—achieving 99.4% spoof detection accuracy and RLWE fault tolerance against ‐stable noise. Our work integrates lattice cryptography, quantum machine learning (QML), and information theory to reshape voice security models for the quantum age. The proposed RLWE based cryptosystem obtained 98.6% encryption fidelity and 95.2% spoof detection on real‐world datasets, which is 6%–7% more accurate and 10%–12% more reliable against quantum noise compared to classical baselines.
ABSTRACT The intersection of quantum computing and voice technology offers unparalleled security challenges and opportunities. In this paper, we propose quantum voice security as an interdisciplinary research field, bridging vulnerabilities where quantum algorithms breach classical voice protection mechanisms while enabling new defense mechanisms. We define a mathematical model for quantum based threats: (1) As cryptographic collapse by Shor's algorithm, breaching RSA/ECC (elliptic‐curve cryptography) protected voice biometrics and communications in polynomial time, enabling store now, decrypt later (SNDL) attacks; (2) As in adversarial amplification by Grover optimized perturbations in Fock space using entanglement monogamy for cross‐model transferability; (3) In biometric spoofing , by relativistic Quantum Generative Adversarial Networks (RQGANs), producing voiceprints indistinguishable from validated data under trace distance (TD) metrics. Concurrently, we define post‐quantum mitigation solutions: (i) In lattice based cryptosystems , (RLWE (Ring Learning With Errors) with ‐bit strength) safeguarding voiceprint encryption against quantum decoherence; (ii) in quantum based detection , by Wigner function negativity () and holographic entropy bound violation () to identify deepfakes; (iii) In hybrid authentication protocols (e.g., entanglement‐swapped TLS‐QUIC (Transport Layer Security over QUIC)) with composable security . Experimental results on multiple audio datasets ( LibriSpeech , Brahms ) validate quantum vulnerabilities—achieving 99.4% spoof detection accuracy and RLWE fault tolerance against ‐stable noise. Our work integrates lattice cryptography, quantum machine learning (QML), and information theory to reshape voice security models for the quantum age. The proposed RLWE based cryptosystem obtained 98.6% encryption fidelity and 95.2% spoof detection on real‐world datasets, which is 6%–7% more accurate and 10%–12% more reliable against quantum noise compared to classical baselines.
Quantum computing represents a fundamental shift in computational capability, using quantum mechanical principles, such as superposition, entanglement, and interference, in order to process information exponentially faster than classical systems. Unlike traditional computers that manipulate bits as 0s and 1s, quantum computers harness qubits that exist in probabilistic superposition states, enabling exploration of multiple solutions at the same time. While this advancement promises transformative applications in molecular modeling, optimization, and machine learning, it also threatens the cryptographic foundations securing modern digital infrastructure. The security of modern-day systems relies on mathematical problems that are not easily solvable for classical computers. Quantum algorithms, particularly Shor’s Algorithm and Grover’s Algorithm, render current asymmetric and symmetric encryption protocols computationally vulnerable; critically, the “Harvest Now, Decrypt Later” strategy transforms present-day communications into long-term security liabilities affecting government, financial, healthcare, and critical infrastructure sectors. To address this threat, this paper evaluates post-quantum cryptographic defenses and proposes Quantum Key Distribution (QKD) as the optimal security framework. Unlike mathematical approaches vulnerable to algorithmic advances, QKD anchors security in the No-Cloning theorem and wave-function collapse, ensuring that eavesdropping attempts introduce detectable anomalies, enabling real-time threat detection. Through comparative analysis of scalability, deployment feasibility, and cost efficiency, this paper demonstrates that QKD provides the most robust, future-proof mechanism for protecting sensitive data transmission in the quantum era, offering a critical blueprint for resilient network defense against emerging computational threats.
As artificial intelligence (AI) systems increasingly underpin critical applications in healthcare, finance, defense, and infrastructure, ensuring their security has become paramount. However, the rapid advancement of quantum computing poses a significant threat to classical cryptographic schemes that currently safeguard these systems. Quantum algorithms such as Shor’s and Grover’s threaten to undermine the confidentiality, integrity, and authentication of data and models that AI systems depend on. In this context, Post-Quantum Cryptography (PQC) has emerged as a crucial area of research aimed at developing cryptographic algorithms that are secure against both classical and quantum adversaries. This paper investigates the intersection of quantum computing threats and AI system vulnerabilities, highlighting how current security mechanisms may fail in a post-quantum era. We explore various categories of PQC—including lattice-based, hash-based, and multivariate polynomial cryptography—and evaluate their applicability to securing AI systems, particularly in scenarios such as model distribution, federated learning, data encryption, and communication in AI-enabled edge and IoT environments. Through analysis of emerging use cases and proposed architectures, the paper outlines how PQC can be integrated into the AI lifecycle to mitigate quantum-era threats. It also identifies key challenges such as computational overhead, integration complexity, and standardization gaps. The study concludes by outlining future research opportunities, including the development of efficient PQC protocols tailored to AI workloads, the creation of quantum-resilient AI pipelines, and the importance of interdisciplinary collaboration to secure AI’s future.
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’s arrival signals a paradigm shift in computational power that may transform several sectors, including drug discovery, artificial intelligence, materials research, and optimization [2]. However, this transformative potential also presents a significant and imminent threat to cybersecurity. At the heart of this technological shift is the ability of quantum computers to tackle the complex mathematical challenges on which modern public-key cryptography relies. Quantum algorithms, most notably Shor’s algorithm, can break problems such as integer factorization and discrete logarithms far more efficiently than classical approaches. As a result, cryptographic methods that are widely trusted today—including RSA and Elliptic Curve Cryptography (ECC)—could become insecure once large-scale quantum computing becomes a reality[1], [8].This poses a profound challenge to the confidentiality, integrity, and authenticity of digital communications, financial networks, essential infrastructure, and national defense systems [9]. To counter this emerging risk, Post-Quantum Cryptography (PQC) has become an important area of active research. The goal of PQC is to design cryptographic techniques that can withstand attacks from both conventional computers and future quantum systems, thereby preserving long-term data security in the face of advancing quantum technologies [3].A number of promising Post-Quantum Cryptography (PQC) approaches are currently being explored in depth. Among them, lattice-based cryptography has attracted significant interest, as it relies on the computational difficulty of problems like Learning With Errors (LWE) and the Shortest Vector Problem (SVP), offering both robust security assurances and practical efficiency [4], [5]. Hash-based signature schemes, such as XMSS and SPHINCS+, offer security rooted in well-established hashing techniques and stateless signature construction [7]. Additionally, code-based cryptography, including systems inspired by the McEliece cryptosystem, remains attractive for its long-standing resistance to cryptanalytic attacks [6]. Other avenues include multivariate quadratic systems and isogeny-based cryptography, each presenting unique benefits and trade-offs in terms of key size, performance, and security robustness [8].A central force driving global standardization is the NIST Post-Quantum Cryptography Standardization Project, initiated in 2016 to evaluate and establish new quantum-resilient cryptographic standards [3]. Several algorithms have already advanced to the final standardization phase, while others remain candidates for further evaluation.Despite this progress, transitioning to PQC introduces practical challenges. Integrating new cryptographic algorithms into current digital ecosystems demands considerable computational and infrastructural updates, often involving larger key sizes and increased processing overhead [10]. Organizations must also ensure crypto-agility, the capability to rapidly adapt cryptographic systems as new standards evolve or vulnerabilities are identified [11].One strategic transition approach involves hybrid cryptographic architectures, which combine conventional and quantum-safe algorithms to provide layered security during this migration period [9]. Moreover, organizations should inventory existing cryptographic assets, conduct quantum risk assessments, pilot PQC deployments, and cultivate a quantum-aware cybersecurity workforce.The threat is amplified by “harvest now, decrypt later” strategies, in which adversaries intercept encrypted data today with the intention of decrypting it once quantum capabilities mature [9]. Particularly sensitive categories — including military communications, governmental archives, personal healthcare records, and intellectual property — require immediate PQC-oriented protection.As the quantum era approaches, coordinated global action is essential to harness quantum innovation while safeguarding digital trust. Through proactive investment in research, standardization efforts, and phased post-quantum deployment, societies can preserve digital sovereignty and security resilience in the face of this technological shift [11].
A significant problem facing cybersecurity is that most client/server identity authentication schemes depend on computational complexity which is recently challenged by the super exponential computational abilities of quantum computers. Quantum cryptography with its quantum mechanics principles solves this problem and provides mathematically un-hackable secure communication for the quantum computers epoch. Biometric authentication has a big challenge related to its protection as it has to be submitted and stored in encrypted form. Unfortunately, most existing biometric cryptosystems rely on classical cryptography, so they are insecure in quantum era. This problem is solved in this paper by introducing a novel three-factor biometric quantum identity authentication scheme combining something you know (password), something you produce (client’s voice), and something you are (client’s face image) is proposed. The scheme consists of two phases: client enrollment and client login/authentication. The methodology is to use in the enrollment phase, two layers of quantum encryption for the client’s voice signal. Each layer consists of two simple quantum circuits of SWAP and C-NOT quantum gates respectively using a different pseudorandom key obtained from a cellular automata (CA) pseudorandom generator. The proposed scheme has many merits. Firstly, it introduces a new design of muti-factors quantum biometric authentication scheme as the biometric voice data is processed, transmitted, and stored at the server database in an encrypted unconditionally secure quantum form which provides parallel processing, real-time communications, inherent level of security against attacks, tamper-proof security and exponential powerful storage capability due to the quantum properties. Secondly, the proposed scheme achieves double-layers security by combing quantum voice encryption and quantum secure direct communication in one process such that the quantum channel eavesdropper cannot obtain any valuable information in case of information leakage. Thirdly, the distribution and management of encryption key problem is solved as there is no need for key exchange prior to communication. Fourthly, it achieves high communication efficiency as although it is a three-factor biometric identity authentication, only one biometric data is sent in quantum encrypted form to the server. Fifthly, the numerical simulations showed that the proposed scheme has large key space, high key sensitivity and more robust performance against different types of attacks compared to other existing classical and quantum voice encryption schemes. Finally, as an identity authentication method, the proposed scheme achieves identification accuracy of 100% with zero False Rejection Rate (FRR) and zero False acceptance rate (FAR) which is perfect.
As quantum computing advances toward practical use, classical cryptography is at a serious risk of being compromised, especially with the use of quantum algorithms like the Shor algorithm, which can break RSA in polynomial time, as well as Elliptic Curve Cryptography (ECC). This research paper highlights the urgent need to protect electronic communications against quantum attacks by leveraging two novel approaches: Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC). The study aims to evaluate the effectiveness, scalability, and integration possibility of these technologies separately and in mixed combinations, to achieve long-term resilient cybersecurity. This research is a mixed-methods study that combines literature analysis, expert surveys, and performance benchmarking to determine the strength of encryption, compatibility with the network, and feasibility in the real world. First-hand information was gathered through structured surveys among cybersecurity professionals and scholars. In contrast, second-hand information was retrieved from peer-reviewed journals and official standards of institutions, such as NIST. It has been found that QKD offers unparalleled information-theoretic security, founded on quantum mechanics, yet has limitations in terms of scale and cost. PQC algorithms, however, especially lattice-based cryptography, are simpler to integrate into a classical infrastructure but present a performance issue on hardware with limited capabilities. Based on the study, a hybridized cryptographic model appears to be the best solution to the current approach of implementing the secure key exchange properties of QKD and the universal properties of PQC, without compromising either.