gr-PHYSEC：用于物理层安全无线通信的实时基于信道的密钥生成
gr-PHYSEC: Real-time Channel-based Key Generation for Physical Layer Secure Wireless Communications
- Florida Atlantic University（佛罗里达大西洋大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
gr-PHYSEC利用GNU Radio和神经网络从无线信道随机性实时生成对称密钥，经Reed-Solomon和SHA-512处理，实验验证低不一致率和高随机性，推动软件定义安全通信。
AI中文摘要：
保护无线通信免受窃听至关重要，尤其是在动态和去中心化的环境中。我们提出了gr-PHYSEC，一个用于实时物理层密钥生成的新型GNU Radio外部（OOT）模块。与依赖预共享密钥或计算复杂度的传统密钥生成不同，我们的方法从无线信道的固有随机性中推导出对称密钥。我们在GNU Radio中嵌入了一个训练好的神经网络，以在探测交换期间提取可信方（Alice和Bob）之间的信道特征。这些特征被量化为二进制密钥，通过Reed-Solomon编码进行协调，并进一步使用SHA-512哈希进行安全处理。生成的密钥随后直接用于加密数据。在FAU CAAI连接机器人测试平台上使用ADALM Pluto软件定义无线电和NVIDIA Jetson Orin进行的真实世界实验，通过地面机器人平台验证了该方法。结果表明，密钥不一致率低且随机性强，这已通过用于加密应用的随机和伪随机数生成器的NIST测试套件验证。该集成展示了GNU Radio如何支持实时AI驱动的安全解决方案，推动了软件定义安全通信的边界。该项目的源代码可在以下网址获取：此https URL。
英文摘要：
Securing wireless communication against eavesdropping is critical, particularly in dynamic and decentralized environments. We present gr-PHYSEC, a new GNU Radio out-of-tree (OOT) module for real-time physical-layer key generation. Unlike traditional key generation that relies on pre-shared secrets or computational complexity, our approach derives symmetric keys from the wireless channel's inherent randomness. We embed a trained neural network within GNU Radio to extract channel features between trusted parties (Alice and Bob) during probe exchanges. These features are quantized into binary keys, reconciled via Reed-Solomon encoding, and further secured with SHA-512 hashing. The generated keys are then directly used to encrypt data. Real-world experiments at the FAU CAAI connected robotics testbed using ADALM Pluto software-defined radios and NVIDIA Jetson Orin validate the approach with ground robotic platforms. Results demonstrate low key disagreement rates and strong randomness, as verified by the NIST test suite for random and pseudorandom number generators for cryptographic applications. This integration showcases how GNU Radio can support real-time AI-driven security solutions, pushing the boundaries of software-defined secure communication. The source code for this project is available at: https://github.com/C2A2-at-Florida-Atlantic-University/gr-PHYSEC
