Post-quantum Federated Learning: Secure And Scalable Threat Intelligence For Collaborative Cyber Defense

Fuente: arXiv
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Main Authors: Nayak, Prabhudarshi, Thiyagarajan, Gogulakrishnan, Mishra, Ritunsa, Bist, Vinay
Format: Preprint
Published: 2026
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author Nayak, Prabhudarshi
Thiyagarajan, Gogulakrishnan
Mishra, Ritunsa
Bist, Vinay
author_facet Nayak, Prabhudarshi
Thiyagarajan, Gogulakrishnan
Mishra, Ritunsa
Bist, Vinay
contents Collaborative threat intelligence via federated learning (FL) faces critical risks from quantum computing, which can compromise classical encryption methods. This study proposes a quantum-secure FL framework using post-quantum cryptography (PQC) to protect cross-organizational data sharing. We expose vulnerabilities in traditional FL through simulated quantum attacks on RSA encrypted gradients and introduce a hybrid architecture integrating NIST-standardized algorithms CRYSTALS-Kyber for key exchange and CRYSTALS-Dilithium for authentication. Testing on APT attack datasets demonstrated 97.6% threat detection accuracy with minimal latency overhead (18.7%), validating real-world viability. A healthcare consortium case study confirmed secure ransomware indicator sharing without breaching privacy regulations. The work highlights the urgency of quantum ready defenses and provides technical guidelines for deploying PQC in FL systems, alongside policy recommendations for standardizing quantum resilience in threat-sharing networks.
format Preprint
id arxiv_https___arxiv_org_abs_2603_07726
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Post-quantum Federated Learning: Secure And Scalable Threat Intelligence For Collaborative Cyber Defense
Nayak, Prabhudarshi
Thiyagarajan, Gogulakrishnan
Mishra, Ritunsa
Bist, Vinay
Cryptography and Security
D.4.6; K.6.5
Collaborative threat intelligence via federated learning (FL) faces critical risks from quantum computing, which can compromise classical encryption methods. This study proposes a quantum-secure FL framework using post-quantum cryptography (PQC) to protect cross-organizational data sharing. We expose vulnerabilities in traditional FL through simulated quantum attacks on RSA encrypted gradients and introduce a hybrid architecture integrating NIST-standardized algorithms CRYSTALS-Kyber for key exchange and CRYSTALS-Dilithium for authentication. Testing on APT attack datasets demonstrated 97.6% threat detection accuracy with minimal latency overhead (18.7%), validating real-world viability. A healthcare consortium case study confirmed secure ransomware indicator sharing without breaching privacy regulations. The work highlights the urgency of quantum ready defenses and provides technical guidelines for deploying PQC in FL systems, alongside policy recommendations for standardizing quantum resilience in threat-sharing networks.
title Post-quantum Federated Learning: Secure And Scalable Threat Intelligence For Collaborative Cyber Defense
topic Cryptography and Security
D.4.6; K.6.5
url https://arxiv.org/abs/2603.07726