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.
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.
Physical layer-based secret key generation has garnered significant attention due to its inherent advantages of lightweight implementation, information-theoretic security, and broad applicability for mobile devices. The reciprocal randomness of the wireless channel ensures the consistent generation of secret bits between two communicating parties. However, it also suffers from the degradation of the efficiency of key generation attributed to the adverse impact of ambient noise, despite sustained efforts to mitigate the inconsistency during quantization. We find that a slight perturbation of the pilot signal, without affecting the correct reception of data frames, induces a corresponding change in the channel response, making it possibly adaptable to the target quantization strategies, thereby reducing the probability of key mismatch. Therefore, we take a different viewpoint on proactive contamination of the pilot signals to obtain the desired channel measurements for accurate physical layer secret key generation. Specifically, we design an adaptive pilot manipulation to avoid the expected channel measurements being too close to the quantization thresholds, enabling high quantization consistency. Furthermore, we also develop a random cross-threshold mechanism to prevent attackers from inferring the quantization results by monitoring the trend of pilot signal variations. A reliable long training sequence (LTS) modification mechanism is incorporated into our method to ensure communication performance by adaptively adjusting the scale of the pilot signal. To validate the effectiveness of our proposed method, we implement a prototype by re-configuring software modules in GNU radio running on the USRP platform. Extensive experiments demonstrate that our scheme outperforms existing representative quantization schemes with better key generation performance.
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 1.7msec. Moreover, theoretical analyses and experiments also confirm the security of the SIM-SKG method against various attacks.
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.
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.
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.
As aspects of our daily lives become more interconnected with the emergence of the Internet of Things (IoT), it is imperative that our devices are reliable and secure from threats. Vulnerabilities of Wi-Fi Protected Access (WPA/WPA2) have been exposed in the past, motivating the use of multiple security techniques, even with the release of WPA3. Physical layer security leverages existing components of communication systems to enable methods of protecting devices that are well-suited for IoT applications. In this work, we provide a low-complexity technique for generating secret keys at the Physical layer to enable improved IoT security. We leverage the existing carrier frequency offset (CFO) and channel estimation components of Orthogonal Frequency Division Multiplexing (OFDM) receivers for an efficient approach. The key generation algorithm we propose focuses on the unique CFO and channel experienced between a pair of desired nodes, and to the best of our understanding, the combination of the features has not been examined previously for the purpose of secret key generation. Our techniques are appropriate for IoT devices, as they do not require extensive processing capabilities and are based on second order statistics. We obtain experimental results using USRP N210 software defined radios and analyze the performance of our methods in post-processing. Our techniques improve the capability of desired nodes to establish matching secret keys, while hindering the threat of an eavesdropper, and are useful for protecting future IoT devices.