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IEEE Transactions on Mobile Computing

Physical Layer Secret Key Generation Leveraging Variable-Length Segment Matching in Wireless Networks

Yicong Du, Huan Dai, Yuchen Su, Haitao Jia, Shuai Li, Yanzhi Ren, Hongbo Liu

Published Mar 6, 2026• 1 citation
Publisher

Abstract

Physical layer secret key generation has emerged as a promising approach for secret key establishment in wireless networks. Unlike traditional quantization-based methods, recent studies have explored matching the patterns of segmented channel samples of equal length for key agreement. However, equal-length segmentation either suffers from inconsistencies between users for short segments or a reduced key generation rate for long ones. To address these issues, we propose a Variable-length Segment Matching-based Secret Key Generation method, VSM-SKG, which adaptively partitions channel samples into variable-length segments to enhance overall matching accuracy, key generation rate, and encryption strength. Specifically, we introduce a dissimilarity-enhanced segmentation and calibration strategy that partitions channel samples into variable-length segments to enlarge segment-wise dissimilarity. To achieve consistent key recovery between users, we develop a dynamic path-aware key generation method that identifies potential segmentation patterns and generates agreed-upon secret keys using a recursive approach combined with a fast retrieval mechanism. Theoretical analyses and real-world experiments validate the attributes of VSM-SKG in terms of accuracy, efficiency, and security in key generation.

DOI
10.1109/tmc.2026.3670938

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Physical layer secret key generation has emerged as a promising approach for secret key establishment in wireless networks. Unlike traditional quantization-based methods, recent studies have explored matching the patterns of segmented channel samples of equal length for key agreement. However, equal-length segmentation either suffers from inconsistencies between users for short segments or a reduced key generation rate for long ones. To address these issues, we propose a Variable-length Segment Matching-based Secret Key Generation method, VSM-SKG, which adaptively partitions channel samples into variable-length segments to enhance overall matching accuracy, key generation rate, and encryption strength. Specifically, we introduce a dissimilarity-enhanced segmentation and calibration strategy that partitions channel samples into variable-length segments to enlarge segment-wise dissimilarity. To achieve consistent key recovery between users, we develop a dynamic path-aware key generation method that identifies potential segmentation patterns and generates agreed-upon secret keys using a recursive approach combined with a fast retrieval mechanism. Theoretical analyses and real-world experiments validate the attributes of VSM-SKG in terms of accuracy, efficiency, and security in key generation.
Secret key generation exploiting inherent channel randomness stands as an important paradigm for physical-layer security in wireless networks. However, existing work relying on quantization has some difficulties in eliminating inconsistent key bits due to the impact of ambient noise. Recent studies propose to match the segmented channel samples (i.e., channel episodes) of similar variation patterns between legitimate peers to achieve error-free key generation, but they also suffer from high computational overhead and reduced accuracy for large key lengths. This work proposes a secret key generation method based on sorted indices matching (SIM-SKG), aiming at efficient and error-free key generation. Specifically, we sort the channel samples to ensure each channel episode with a unique variation pattern for accurate matching. To avoid the impact of half-duplex communication mode and ambient noise, we propose to match the indices instead of the channel samples as in existing studies. We also develop a noise perturbation scheme that further mitigates the ambiguity during indices matching. Extensive experimental studies demonstrate the high efficiency and accuracy of SIM-SKG under various scenarios for both RSS and CSI channel measurements. Specifically, SIM-SKG achieves error-free key generation with a length of 2048 bits within as little as 1.7msecmsecmsec. Moreover, theoretical analyses and experiments also confirm the security of the SIM-SKG method against various attacks.
As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.
Secret key generation plays an important role in device-to-device communication security in wireless networks. For consistent key generation between two communicating parties, existing matching-based key generation methods match segmented channel measurements (channel episodes) of similar patterns between two parties. However, these methods suffer diminished accuracy for large key lengths or in the presence of ambient noise. This work takes a different perspective to produce the desired channel measurements through adaptive manipulation of pilot signals for robust and accurate physical layer secret key generation. Specifically, an adaptive pilot manipulation scheme is designed not only to ensure that each channel episode has a unique pattern but also to improve pattern similarity between a pair of matched channel episodes, thus enabling high matching consistency. To validate the effectiveness of our method, we implement it by re-configuring software modules in GNU radio running on the USRP platform. Extensive experiments demonstrate that our method outperforms existing representative quantization-based and matching-based methods with improved key generation performance.
The physical layer secret key generation exploiting wireless channel reciprocity has attracted considerable attention in the past two decades. On-going research have demonstrated its viability in various radio frequency (RF) systems. Most of existing work rely on quantization technique to convert channel measurements into digital binaries that are suitable for secret key generation. However, non-simultaneous packet exchanges in time division duplex systems and noise effects in practice usually create random channel measurements between two users, leading to inconsistent quantization results and mismatched secret bits. While significant efforts were spent in recent research to mitigate such non-reciprocity, no efficient method has been found yet. Unlike existing quantization-based approaches, we take a different viewpoint and perform the secret key agreement by solving a bipartite graph matching problem. Specifically, an efficient dual-permutation secret key generation method, DP-SKG, is developed to match the randomly permuted channel measurements between a pair of users by minimizing their discrepancy holistically. DP-SKG allows two users to generate the same secret key based on the permutation order of channel measurements despite the non-reciprocity over wireless channels. Extensive experimental results show that DP-SKG could achieve error-free key agreement on received signal strength (RSS) with a low cost under various scenarios.
The physical layer secret key generation exploiting wireless channel reciprocity has demonstrated its viability and effectiveness in various wireless scenarios, such as the Internet of Things (IoT) network, mobile communication network, and industrial control system. Most of the existing studies rely on the quantization technique to convert channel measurements into secret bits for confidential communications. However, non-simultaneous packet exchanges in time-division duplex systems and noise effects usually induce inconsistent quantization results and mismatched secret bits. Although recent research has spent significant effort mitigating such non-reciprocity, it is still far from practical error-free key generation. Unlike previous quantization-based approaches, we take a different viewpoint to match the randomly manipulated (i.e., permuted or edited) channel measurements between a pair of users by minimizing their discrepancy holistically. Specifically, two novel secret key generation algorithms based on bipartite graph matching (BMSKG) and edited sequence alignment (SA-SKG) are developed. BM-SKG allows two users to generate the same secret key based on the permutation order of channel measurements, while SASKG aims to align the edited channel measurements between a pair of users for secret key agreement. In both algorithms, one user can preset the secret key and embed encrypted messages in the exchanged data packets, which reduces communication overheads in key generation. Extensive experimental results show that both BM-SKG and SA-SKG algorithms achieve error-free key agreement on channel measurements at a low cost under various scenarios.
In the rapidly evolving landscape of wireless communication, securing transmitted information remains a critical challenge. This study provides a comprehensive review of secret key generation (SKG) techniques designed to secure physical layer wireless communication channels. We focus on key generation methods that exploit physical layer characteristics such as channel state information, received signal strength, and bit error rate. The computational complexity of these techniques is also examined, emphasizing the trade-offs between security and efficiency for real-world implementations. The review identifies open challenges such as developing low-cost, resource-efficient systems, managing artificial noise, and addressing the impact of mobility and multiuser massive MIMO systems on SKG rates. Our findings aim to guide the development of more efficient, scalable SKG methods for next-generation wireless networks. Additionally, we propose a method for securely generating identical secret keys between nodes using Cuckoo filters and a Map-Reduce model for frame hashing, ensuring long-term security in IoT environments.