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.

翻译：通过联邦学习（FL）实现的协同威胁情报面临来自量子计算的关键风险，后者可能破坏经典加密方法。本研究提出一种采用后量子密码学（PQC）的量子安全FL框架，以保护跨组织数据共享。我们通过对RSA加密梯度进行模拟量子攻击，揭示了传统FL中的漏洞，并引入一种混合架构，该架构集成了用于密钥交换的NIST标准化算法CRYSTALS-Kyber和用于身份验证的CRYSTALS-Dilithium。在APT攻击数据集上的测试表明，该框架实现了97.6%的威胁检测准确率，且延迟开销极低（18.7%），验证了其实际可行性。一项医疗联盟案例研究证实了其在遵守隐私法规的前提下安全共享勒索软件指标的能力。本工作强调了量子就绪防御的紧迫性，为在FL系统中部署PQC提供了技术指南，并就威胁共享网络中量子抗性的标准化提出了政策建议。