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.
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.
The advent of quantum computing poses a profound threat to traditional cryptographic systems, exposing vulnerabilities that compromise the security of digital communication channels reliant on RSA, ECC, and similar classical encryption methods. Quantum algorithms, notably Shor's algorithm, exploit the inherent computational power of quantum computers to efficiently solve mathematical problems underlying these cryptographic schemes. In response, post-quantum cryptography (PQC) emerged as a critical field aimed at developing resilient cryptographic algorithms impervious to quantum attacks. This paper delineates the vulnerabilities of classical cryptographic systems to quantum attacks, elucidates the principles of quantum computing, and introduces various PQC algorithms such as lattice-based cryptography, code-based cryptography, hash-based cryptography, and multivariate polynomial cryptography. Highlighting the importance of PQC in securing digital communication amidst quantum computing advancements, this research underscores its pivotal role in safeguarding data integrity, confidentiality, and authenticity in the face of emerging quantum threats.
The integration of Artificial Intelligence (AI) in Internet of Things (IoT) financial systems has ushered in a new era of autonomous decision-making, real-time analytics, and dynamic financial interactions. However, the advent of quantum computing presents an imminent threat to the cryptographic foundations of these systems, jeopardizing data confidentiality, transaction integrity, and system authenticity. This paper explores quantum-resistant cryptographic mechanisms—particularly lattice-based, hash-based, and multivariate polynomial cryptography—as viable defenses against quantum attacks on AI-powered IoT financial networks. The study reviews the vulnerabilities introduced by quantum algorithms such as Shor’s and Grover’s, assesses the performance and scalability of post-quantum cryptographic (PQC) protocols in real-world IoT financial deployments, and presents an optimized framework that balances cryptographic strength with computational feasibility. A hybrid security architecture is proposed, integrating PQC with AI-based anomaly detection to ensure end-to-end trust, resilience, and compliance with emerging quantum-secure standards. Through simulations and case-based evaluations, the findings underscore the critical importance of immediate cryptographic transition planning to safeguard future financial infrastructures.
The emergence of quantum computing poses a serious threat to traditional communication systems, endangering the security of digital communications and critical infrastructure. Although existing cryptographic algorithms (such as RSA and ECC) rely on the inefficiency of computing large numbers or solving logarithm inequality problems, quantum algorithms (especially Shor's algorithm) can solve these problems efficiently. To mitigate this threat, the field of post-quantum cryptography (PQC) has emerged and focuses on developing cryptographic systems that are resilient to quantum attacks. The main techniques in PQC include lattice-based, hash-based, code-based, and multivariate polynomial cryptography. Lattice-based cryptography is the leading contender, providing high security and supporting good properties such as fully homomorphic encryption, but facing issues related to size and computational efficiency. Hash-based encryption enables strong digital signatures but has limitations. Code-based encryption based on error-correcting codes provides proof of security but requires small size. Multivariate polynomial cryptography has good performance but has drawbacks in some applications. While standardization efforts led by organizations such as NIST continue, PQC is at the forefront of protecting the digital future from the impact of quantum computing, ensuring the integrity and confidentiality of information in the post-quantum era.
Current cryptographic systems, heavily reliant on classical algorithms, are increasingly vulnerable to the formidable capabilities of quantum computing. Notably, quantum algorithms such as Shor’s and Grover’s pose profound threats by accelerating decryption processes, which could soon make existing cryptosystems ineffective. This paper stresses the critical need and complexity of shifting to Post-Quantum Cryptography (PQC) to safeguard encrypted communications against these emerging quantum threats. It outlines the timeline of the National Institute of Standards and Technology’s (NIST) efforts in standardizing PQC, elucidating the significant challenges and the essential nature of adopting these new standards. While NIST provides structured guidance, transitioning to PQC presents substantial risks and difficulties, particularly in terms of organizational adaptation and the technical overhaul required. The discourse further explores the tangible implications of quantum advancements on both symmetric and asymmetric key cryptography, highlighting the potential vulnerabilities and the increased risk of security breaches. The paper underscores the imperative for immediate action in initiating the transition towards robust PQC systems, given the rapid development and anticipated deployment of quantum computing technologies capable of decrypting currently secure information. This transition is not merely a technical upgrade but a crucial strategic move to preemptively counteract quantum threats, ensuring the continued confidentiality and integrity of sensitive data across various sectors.
The integration of artificial intelligence (AI) and machine learning (ML) into critical infrastructure has raised urgent concerns about data and model security, particularly in light of emerging quantum computing capabilities. Quantum algorithms threaten to render classical cryptographic methods obsolete, exposing AI/ML systems to potential breaches in confidentiality, integrity, and availability. This paper investigates the implications of quantum computing for securing AI/ML data both in transit and at rest and explores the development of quantum-safe networking protocols and cryptographic techniques. I examine post-quantum cryptographic (PQC) solutions including lattice-based, code-based, and hash-based algorithms, alongside the role of quantum key distribution (QKD) and AI-enhanced security orchestration. The study further addresses secure edge intelligence, federated AI systems, and emerging standards for 6G and beyond. My findings highlight both the necessity and complexity of transitioning to quantum-resilient infrastructure. Key challenges include computational overhead, legacy interoperability, and ethical concerns around AI-powered surveillance in quantum-secured environments. The paper concludes by emphasizing the need for proactive policy, investment in quantum-safe R&D, and cross-sector collaboration to safeguard AI/ML infrastructure in the post-quantum era.
Classical cryptographic have a threat because of the emergence of quantum computing, and hence there is an urgent need to research post-quantum cryptography. To evaluate the potential of post-quantum encryption algorithms in countering quantum threats, here the study sees how they can be integrated with artificial intelligence (AI) and machine learning (ML). For their theoretical quantum resistance, the study looks at established post-quantum cryptography methods such as lattice-based, hash-based, and multivariate cryptographic schemes. A review of current research also simulation-based research is also taken into account to review the potential of AI/ML in bolstering security protocols and simplifying encryption processes. The key takeaway is that machine learning and AI do have actual potential to enhance post-quantum encryption through increasing its efficiency, flexibility, and resistance to future quantum attacks. AI also assists in real-time responsiveness in avoiding possible vulnerabilities. Our work contributes to the growing literature by combining insights from cryptographic and AI/ML research, providing a comprehensive evaluation of post-quantum encryption methods. This study emphasizes the highest importance of adopting hybrid cryptography techniques in order to advance information security in the quantum era, leading to further research in practical applications.