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A Survey of Quantum-Proofing LLMs and Agentic AI: Security Threats, Post-Quantum Cryptography, and Open Challenges

Mehran Mozaffari Kermani

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.2139/ssrn.7576261

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A Survey of Quantum-Proofing LLMs and Agentic AI: Security Threats, Post-Quantum Cryptography, and Open Challenges

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The rapid evolution of communication networks, driven by the expansion of heterogeneous environments such as 6G, Internet of Things (IoT), and edge computing, has exposed a critical research gap in the lack of unified frameworks that jointly address intelligent network control and quantum-resilient security. Existing networking protocols were originally designed under static configurations and classical security assumptions, making them increasingly inadequate for dynamic, large-scale, and intelligent infrastructures exposed to quantum-enabled threats. At the same time, the emergence of Quantum Computing (QC) introduces severe security risks, as widely used cryptographic mechanisms supporting protocols such as Transport Layer Security (TLS) and Internet Protocol Security (IPsec) become vulnerable to quantum attacks. This paper presents a structured survey based on a systematic classification of recent literature across AI-enabled networking, Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD), and protocol-level integration approaches. The review categorizes existing works into AI-driven network optimization, quantum-resilient security mechanisms, and hybrid AI–QRC architectural frameworks, enabling a unified comparison of design strategies and deployment models. Furthermore, this survey analyzes how Artificial Intelligence (AI) techniques enable autonomous network operations while Quantum-Resilient Cryptography (QRC) approaches provide post-quantum security guarantees, highlighting their complementary roles in next-generation network design. The study further synthesizes key findings for a tightly coupled AI–QRC co-design, which remains an open challenge due to mismatched assumptions in control latency, cryptographic overhead, and protocol adaptability. Additionally, this review emphasizes the need for integrated frameworks that combine intelligence and quantum security to develop adaptive, scalable, and resilient network protocols for the post-quantum era.
The rapid deployment of AI models necessitates robust, quantum-resistant security, particularly against adversarial threats. Here, we present a novel integration of post-quantum cryptography (PQC) and zero trust architecture (ZTA), formally grounded in category theory, to secure AI model access. Our framework uniquely models cryptographic workflows as morphisms and trust policies as functors, enabling fine-grained, adaptive trust and micro-segmentation for lattice-based PQC primitives. This approach offers enhanced protection against adversarial AI threats. We demonstrate its efficacy through a concrete ESP32-based implementation, validating a crypto-agile transition with quantifiable performance and security improvements, underpinned by categorical proofs for AI security. The implementation achieves significant memory efficiency on ESP32, with the agent utilizing 91.86% and the broker 97.88% of free heap after cryptographic operations, and successfully rejects 100% of unauthorized access attempts with sub-millisecond average latency.