CKM-Assisted Physical-Layer Security for Resilience Against Unknown Eavesdropping Location
Ladan Khaloopour, Matthias Hollick, Vahid Jamali

TL;DR
This paper introduces a CKM-based approach to enhance physical-layer security in mmWave communications, optimizing beam and power allocation without knowing the eavesdropper's position, thus improving resilience against unknown threats.
Contribution
It proposes a novel CKM-assisted algorithm for secure beam and power allocation that does not rely on eavesdropper location or channel information.
Findings
Maximized secrecy rate under worst-case eavesdropper scenarios
Developed an efficient algorithm for time and power allocation
Enhanced physical-layer security using CKM in mmWave systems
Abstract
Channel Knowledge Map (CKM) is an emerging data-driven toolbox that captures our awareness of the wireless channel and enables efficient communication and resource allocation beyond the state of the art. In this work, we consider CKM for improving physical-layer security (PLS) in the presence of a passive eavesdropper (Eve), without making any assumptions about Eve's location or channel state information (CSI). We employ highly directional mmWave transmissions, with the confidential message jointly encoded across multiple beams. By exploiting CKM, we derive an algorithm for time and power allocation among the beams that maximizes the absolute secrecy rate under the worst-case scenario for Eve's location.
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