Harvesting Physical-Layer Randomness in Millimeter Wave Bands
The unpredictability of the wireless channel has been used as a natural source of randomness to build physical-layer security primitives for shared key generation, authentication, access control, proximity verification, and other security properties. Compared to pseudo-random generators, it has the potential to achieve information-theoretic security. In sub-6 GHz frequencies, the randomness is harvested from the small-scale fading effects of RF signal propagation in rich scattering environments. However, the RF propagation characteristics follow sparse models with clustered paths when devices operate in millimeter-wave (mmWave) bands (5G and Next-Generation networks, Wi-Fi in 60GHz). Millimeter-wave transmissions are typically directional to increase the gain and combat high signal attenuation, leading to stable and more predictable channels. In this paper, we first demonstrate that state-of-the-art methods relying on channel state information or received signal strength measurements fail to produce high randomness. Accounting for the unique features of mmWave propagation, we propose a novel randomness extraction mechanism that exploits the random timing of channel blockage to harvest random bits. Compared with the prior art in CSI-based and context-based randomness extraction, our protocol remains secure against <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passive and active Man-in-the-Middle adversaries co-located with the legitimate devices</i>. We demonstrate the security properties of our method in a 28 GHz mmWave testbed in an indoor setting.
Authors
- Yanjun Pan (ORCID: https://orcid.org/0000-0001-6425-7102)
- Loukas Lazos (ORCID: https://orcid.org/0000-0002-6187-7063)
- Jingcheng Li (ORCID: https://orcid.org/0000-0002-6868-3077)
- Ming Li (ORCID: https://orcid.org/0000-0002-6406-1983)
- Ziqi Xu (ORCID: https://orcid.org/0009-0004-4912-4781)
Institutions
- University of Arizona (US)
- University of Arkansas at Fayetteville (US)
Publication Details
- Journal
- IEEE Transactions on Mobile Computing
- Published
- 2024-11-15
- DOI
- https://doi.org/10.1109/tmc.2024.3499876
- Citations
- 2
- Primary Topic
- Millimeter-Wave Propagation and Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.42