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Digital Signal Processing

Efficient reliability-adaptive physical-layer secret key generation

Meixiang Zhang, Thara Son, Sooyoung Kim

Published Oct 10, 2026• 0 citations
Publisher
DOI
10.1016/j.dsp.2026.106563

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Physical layer secret key generation (PHYSKG) is a promising technology to provide lightweight and information-theoretically secure key sharing. It has been widely studied in wireless communications and the Internet of Things (IoT). Yet, this technology is nontrivial for large scale wireless networks due to high overhead, insufficient security, and poor adaptability. Recently, artificial intelligence (AI)-based PHYSKG has shown greater performance and higher security with lower overhead than traditional schemes. Although many existing works have been devoted to exploiting AI-based PHYSKG, a scientific review is still missing, but highly anticipated in the literature. In this article, we perform a serious review on AI-based PHYSKG in wireless communications. After a comprehensive introduction to the processing procedure of AI-based PHYSKG, we propose a set of criteria for justifying its performance with regard to key generation efficiency, reliability, security, and generality. Based on these criteria, we review and analyze the state-of-art, focusing on randomness extraction and quantification. On the basis of the review, we further indicate open issues, current challenges, and future research direction in this field.
Network coding is one of the key technologies to improve the throughput, efficiency, and reliability of two-way relay networks (TWRNs). However, it also brings some new security problems when the physical layer security is considered. In this paper, we present security network coding schemes with key generation from multipath channels to enhance the security performance for TWRN. First, a joint key generation (JKG) approach is proposed, which generates secret keys based on channel impulse responses of multipath channels. Different from the traditional approaches, key exchange is not necessary for the JKG approach such that the eavesdroppers cannot obtain any information about secret keys. Then, an adaptive quantization algorithm is proposed to adaptively choose different parameters for quantization in key generation, which can improve the secret key rate with an acceptable secret key disagreement probability and can still work even if the SNR is low. Finally, security network coding systems are constructed to combine the key generation approaches with the proposed algorithm. Simulation results show that the proposed schemes are valid and secure against wiretap attacks.
Physical layer secret key (PLSK) attracts much research interest in recent years due to its lightweight properties and potential to be used in real internet-of-things (IoT) applications. However, most existing works focus on PLSK generation between pairwise users under passive eavesdropping and lack of design for group key generation especially when active attacks may exist. In this paper, the RObust and LIghtweight Group key generation Against Active Attack (ROLIG3A) scheme is proposed to achieve reliable, efficient, and secure group secret key generation (GSKG) against various malicious attack patterns. In ROLIG3A, adaptive channel listening and dual code channel transmission are designed to avoid legitimate users from jamming signals. Comparing with the exiting GSKG schemes, more proactive countermeasures, back interference cancellation, and ECC-based information sharing are involved to realize the identification and cancellation of malicious attacks. Simulation results show that ROLIG3A has better security performance than the state-of-the-art GSKG schemes in the face of both sabotage attacks and manipulative attacks. In addition, ROLIG3A can provide an acceptable key generation rate and it is reliable even in low signal-to-noise-ratio (SNR) environments.