Skip to content
NewA calmer, faster ZeroHour

gr-PHYSEC: Real-time Channel-based Key Generation for Physical Layer Secure Wireless Communications

arXiv cs.CRby Jose Angel Sanchez Viloria ()1 min read3 · 1 read
AI summary · glm-5.3Summaries by Vani AI

gr-PHYSEC GNU Radio module derives symmetric encryption keys from wireless channel randomness using a neural network, validated on robotic platforms with ADALM-Pluto SDRs.

The paper introduces gr-PHYSEC, a GNU Radio out-of-tree module for real-time physical-layer key generation that derives symmetric keys from the wireless channel's inherent randomness instead of pre-shared secrets. A trained neural network extracts channel features between trusted parties during probe exchanges; features are quantized into binary keys, reconciled via Reed-Solomon encoding, and secured with SHA-512 hashing before direct use for encryption. Real-world experiments at the FAU CAAI connected robotics testbed using ADALM Pluto software-defined radios and NVIDIA Jetson Orin demonstrated low key disagreement rates and NIST-verified randomness. Source code is publicly available on GitHub.

Key facts
  • Neural network extracts channel features for key generation inside GNU Radio
  • Keys reconciled via Reed-Solomon and hashed with SHA-512
  • Validated on ground robots with ADALM Pluto SDRs and Jetson Orin
  • Randomness verified via NIST test suite; code open-sourced
Analyze this story with Vani AIImpact, who is affected and what defenders should do, in a new chat

From the original article

1 min read at arxiv.org

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.

arXiv cs.CR

By Jose Angel Sanchez Viloria · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.