Autor: |
Srinivasan, Muralikrishnan, Skaperas, Sotiris, Chorti, Arsenia |
Rok vydání: |
2021 |
Předmět: |
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Druh dokumentu: |
Working Paper |
Popis: |
This paper presents a systematic approach to use channel state information for authentication and secret key distillation for physical layer security (PLS). We use popular machine learning (ML) methods and signal processing-based approaches to disentangle the large scale fading and be used as a source of uniqueness, from the small scale fading, to be treated as a source of shared entropy secret key generation (SKG). The ML-based approaches are completely unsupervised and hence avoid exhaustive measurement campaigns. We also propose using the Hilbert Schmidt independence criterion (HSIC); our simulation results demonstrate that the extracted stochastic part of the channel state information (CSI) vectors are statistically independent. |
Databáze: |
arXiv |
Externí odkaz: |
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