Secret key generation from wireless channel is an emerging technique to provide secure keys for message encryption. However, the measured channel state information (CSI) requires high reciprocity in order to obtain symmetric keys. In this paper, we propose a novel loop-back transmission scheme for time division duplex (TDD) systems, which is named as LB-TDD. The proposed LB-TDD scheme can effectively reduce the CSI non-reciprocity due to the hardware fingerprint interference and system synchronization offset. We initially discuss the benefits and optimizations of using LB-TDD for CSI reciprocity enhancement. After that, a secret key generation method based on orthogonal frequency division multiplexing (OFDM) probing signals is introduced. Finally, a channel model and a practical universal software radio peripheral (USRP) system is setup for both simulation and experimental verification. Evaluation results show that our proposed LB-TDD scheme can effectively eliminate CSI non-reciprocity for secret key generation.
Secret key generation from wireless channel is an emerging technique to provide secure keys for message encryption. However, the measured channel state information (CSI) requires high reciprocity in order to obtain symmetric keys. In this paper, we propose a novel loop-back transmission scheme for time division duplex (TDD) systems, which is named as LB-TDD. The proposed LB-TDD scheme can effectively reduce the CSI non-reciprocity due to the hardware fingerprint interference and system synchronization offset. We initially discuss the benefits and optimizations of using LB-TDD for CSI reciprocity enhancement. After that, a secret key generation method based on orthogonal frequency division multiplexing (OFDM) probing signals is introduced. Finally, a channel model and a practical universal software radio peripheral (USRP) system is setup for both simulation and experimental verification. Evaluation results show that our proposed LB-TDD scheme can effectively eliminate CSI non-reciprocity for secret key generation.
Physical layer security key generation exploits unpredictable features from wireless channels to achieve high security, which requires high reciprocity in order to set up symmetric keys between two users. This paper investigates enhancing the channel reciprocity using a loop-back scheme with multiple frequency bands in time-division duplex (TDD) communication systems, in order to mitigate the effect of hardware fingerprint interference and synchronization offset. The scheme is evaluated to be robust to passive eavesdropping and active Man-in-the-Middle attack through both theoretical analyses and practical measurements. A secret key generation protocol is subsequently designed. The performance of the proposed secret key generation method is then evaluated through both numerical simulation and experiments. Results demonstrate that the proposed scheme can effectively mitigate non-reciprocity and outperforms the classical TDD scheme in both key disagreement rate and key generation rate.
In physical-layer secret key generation, key generation performance is susceptible to hardware impairments (HIs), which can degrade channel reciprocity. Additionally, the security of loop-back mechanism based schemes in frequency division duplex (FDD) systems requires further enhancement. To address these challenges, this paper proposes a secure key generation scheme based on a loop-back mechanism for FDD systems. By transmitting signals across different frequency bands in a loop-back fashion, the proposed scheme mitigates the adverse effects of HI variations across frequency bands and enhances system security. Theoretical analyses are conducted on the normalized mean square error and the secret key rate of the loop-back mechanism in both FDD and time division duplex (TDD) systems, providing a clear security assessment of the proposed scheme. Simulation and experimental results demonstrate that by accounting for HI differences in the frequency domain, the proposed scheme improves channel reciprocity, enhances the secret key rate, achieves a higher key generation ratio (KGR), and reduces the key disagreement rate (KDR) compared to state-of-the-art methods.
Channel reciprocity is an inherent feature of time division duplex (TDD) system while in frequency division duplex (FDD) system it is limited due to different frequencies being used for the uplink and the downlink. As a consequence, channel reciprocity-based secret generating methods used in TDD systems cannot be applied directly to FDD systems. In this paper, we present a novel secret key generation method for FDD system, for which the communication pair estimate the channel state information (CSI) of the same time in the uplink by a specially designed forwarding strategy and generate the secret key from the CSI estimates. Numerical simulations are implemented to verify the effectiveness of the proposed method.
Physical layer encryption is a promising solution to provide transmission security for Internet-of-Things (IoT). To realize physical layer encryption, channel state information (CSI) as a random source to generate secret keys should be exploited. The reciprocity of wireless channel between legitimate communication nodes which is typically assumed for time division duplex (TDD) systems, is of critical importance to ensure the consistency in generated keys at two nodes. However, in practical TDD systems, due to the asynchronous measurement of CSI, the receiver noise and the the difference in hardware, etc., the reciprocity of channel measurements between legitimate parties is hard to be guaranteed, which makes physical layer key generation approach infeasible. To address this issue, we propose a wireless key generation scheme based on deep learning techniques. Firstly, a feature extraction network, which consists of two auto-encoders trained jointly, is developed to extract the common feature from the different yet correlated channel observations at two legitimate nodes, which will be used as the source to generate keys. Then a quantizer with an adaptive guard band width is devised to output a binary secret-key sequence from the feature vector. Numerical results show that the proposed scheme achieves remarkable improvement in terms of key disagreement rate (KDR) and key generation rate (KGR) compared existing counterparts in the literature.
In recent years, secret key generation based on physical layer security has gradually attracted high attentions. The wireless channel reciprocity and eavesdropping attack are critical problems in secret key generation studies. In this paper, we carry out a simulation and experimental study of channel reciprocity in terms of measuring channel state information (CSI) in both time division duplexing (TDD) and frequency division duplexing (FDD) modes. In simulation study, a close eavesdropping wiretap channel model is introduced to evaluate the security of the CSI by using Pearson correlation coefficient. In experimental study, an indoor wireless CSI measurement system is built with N210 and X310 universal software radio peripheral (USRP) platforms. In TDD mode, theoretical analysis and most of experimental results show that the closer eavesdropping distance, the higher CSI correlation coefficient between eavesdropping channel and legitimate channel. However, in actual environment, when eavesdropping distance is too close (less than 1/4 wavelength), this CSI correlation seriously dropped. In FDD mode, both theoretical analysis and experimental results show that the wireless channel still owns some reciprocity. When frequency interval increases, the FDD channel reciprocity in actual environment is better than that in theoretical analysis.
Physical-layer secret key generation (PSKG) is a well-known and effective method for boosting wireless security in the Internet of Things (IoT). This technique creates cryptographic keys from correlated wireless channel measurements by taking advantage of the reciprocal nature of uplink and downlink channels. However, in time-division duplex (TDD) systems, issues such as hardware imperfection and noise can disrupt channel reciprocity, making the key generation process more difficult. This paper presents a new PSKG approach that tackles these issues by using deep learning to enhance channel reciprocity, even with imperfect channel state information (CSI). Specifically, a denoising sparse autoencoder (DSAE) is introduced to efficiently learn and extract channel reciprocity features in TDD OFDM systems. Furthermore, this study presents a low-complexity DSAE-based PSKG scheme that utilizes the phase of channel frequency responses (CFR) for key generation. The reported results indicate that the proposed DSAE-based PSKG method notably decreases the key disagreement ratio (KDR) while improving randomness, offering a robust and practical solution for securing wireless communications in IoT environments.