Smart Channel State Information Pre-processing for Joint Authentication and Secret Key Distillation
Muralikrishnan Srinivasan, Sotiris Skaperas, Arsenia Chorti, Mahdi, Shakiba Herfeh, Muhammad K. Shehzad, and Philippe Sehier

TL;DR
This paper introduces a novel power domain decomposition method for channel state information that enables simultaneous RF fingerprinting-based authentication and secret key generation, enhancing wireless security.
Contribution
It proposes a unified framework using statistical metrics and machine learning techniques to decompose CSI into components suitable for authentication and key generation.
Findings
Effective separation of predictable and unpredictable CSI components.
Demonstrated improved security guarantees in synthetic and real datasets.
Applicable to future wireless security protocols.
Abstract
While the literature on RF fingerprinting-based authentication and key distillation is vast, the two topics have customarily been studied separately. In this paper, starting from the observation that the wireless channel is a composite, deterministic / stochastic process, we propose a power domain decomposition that allows performing the two tasks simultaneously. We devise intelligent pre-processing schemes to decompose channel state information (CSI) observation vectors into "predictable" and "unpredictable" components. The former, primarily due to large-scale fading, can be used for node authentication through RF fingerprinting. The latter, primarily due to small-scale fading, could be used for semantically secure secret key generation (SKG). To perform the decomposition, we propose: (i) a fingerprint "separability" criterion, expressed through the maximisation of the total variation…
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Taxonomy
TopicsWireless Signal Modulation Classification
MethodsPrincipal Components Analysis
