Categorical Framework for Quantum-Resistant Zero-Trust AI Security

Fuente: arXiv
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Auteurs principaux: Cherkaoui, I., Clarke, C., Horgan, J., Dey, I.
Format: Preprint
Publié: 2025
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author Cherkaoui, I.
Clarke, C.
Horgan, J.
Dey, I.
author_facet Cherkaoui, I.
Clarke, C.
Horgan, J.
Dey, I.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_21768
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Categorical Framework for Quantum-Resistant Zero-Trust AI Security
Cherkaoui, I.
Clarke, C.
Horgan, J.
Dey, I.
Cryptography and Security
Category Theory
Quantum Physics
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.
title Categorical Framework for Quantum-Resistant Zero-Trust AI Security
topic Cryptography and Security
Category Theory
Quantum Physics
url https://arxiv.org/abs/2511.21768