February 13, 2024Open Access

PQC meets ML or AI: Exploring the Synergy of Machine Learning and Post-quantum Cryptography

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Abstract

Artificial Intelligence and Machine Learning are widely integrated into real-world applications, facing security and privacy risks. The emergence of quantum computers poses a substantial threat to ML's long-term security. Our study delves into the intersection of ML with security and privacy in the post-quantum era, where Post-Quantum Cryptography meets ML/AI.

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Cite This Study

Darzi et al. (Tue,) studied this question.

synapsesocial.com/papers/68e79585b6db6435877062d1 https://doi.org/https://doi.org/10.36227/techrxiv.170785010.08081159/v1

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1A Survey of Deep Learning Architectures for Privacy-Preserving Machine Learning With Fully Homomorphic Encryption2022 · 80 citations
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4Towards Quantum-Enhanced Machine Learning for Network Intrusion Detection2020 · 43 citations
5Privacy-Preserving Machine Learning: Threats and Solutions2019 · 444 citations

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