Securing Cryptography in the Age of Quantum Computing and AI: Threats, Implementations, and Strategic Response

2026-03-07

AI Summary

This study addresses the synergistic threat posed by quantum computing and artificial intelligence to current cryptographic systems: Shor’s algorithm can break public-key schemes such as RSA and ECC, while AI-driven side-channel attacks can circumvent physical countermeasures. The paper presents the first systematic evaluation of cryptographic vulnerability under combined quantum–AI attacks and proposes a defense-in-depth framework integrating post-quantum cryptography (ML-KEM/ML-DSA and SLH-DSA), implementation hardening, and cryptographic agility. Findings indicate that lattice-based and hash-based signatures resist known quantum attacks but remain susceptible to side-channel leakage at the implementation layer; symmetric encryption retains security in the quantum setting only if key lengths are doubled to compensate for halved effective strength. This work underscores that cryptographic security must be treated as a continuously evolving process and offers a practical roadmap for mitigating coordinated quantum–AI threats.

Technology Category

• Machine Learning: Quantum Machine Learning
• Computer Vision: Adversarial Attacks & Robustness
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Security and Privacy: Applications of cryptography
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

This review examines how quantum computing and artificial intelligence challenge current cryptographic systems. We analyze the literature to assess the resilience of algorithms against quantum attacks (Shor's and Grover's algorithms) and AI-enhanced cryptanalysis. RSA and elliptic curve cryptography are at risk of compromise from quantum computers. Symmetric algorithms like AES-128 retain security, but with a reduced effective key length under quantum attacks. Deep learning models demonstrate improved side-channel analysis, extracting keys from protected implementations. These convergent threats require a defense-in-depth approach that combines post-quantum algorithms, implementation hardening, and cryptographic agility. We find that lattice-based algorithms (ML-KEM, ML-DSA) resist known quantum attacks but require careful implementation to prevent side-channel leakage. Hash-based signatures (SLH-DSA) provide conservative security with signature sizes ranging from 17 to 50 KB. No single approach addresses both quantum and AI threats comprehensively. Organizations must treat cryptographic security as an ongoing process rather than a fixed deployment, maintaining the capability to update algorithms as threats evolve.

Problem

• quantum computing
• artificial intelligence
• cryptography
• side-channel attacks
• post-quantum security

Innovation

• post-quantum cryptography
• AI-enhanced cryptanalysis
• side-channel resistance
• cryptographic agility
• lattice-based cryptography