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International Conference on Wireless Communications and Signal Processing (WCSP)

An Improved CQA Quantization Algorithm for Physical Layer Secret Key Extraction

Lei Huang, Dengke Guo, Jun Xiong, Dongtang Ma

Published Oct 21, 2020• 11 citations
Publisher

Abstract

With the wide application of wireless sensor network, the security mechanism based on cryptography faces many challenges in computational complexity and security, and physical layer secret key extraction as an alternative solution has been widely studied. To meet the requirements of high key generation rate (KGR) and low key disagreement rate (KDR) in the secret key extraction process, an improved channel quantization alternating (CQA) algorithm is proposed in this paper. The algorithm filtrates the phase values of channel frequency response (CFR) using test results of CFR amplitude values, and then quantizes the reserved phase values by CQA algorithm. Compared to the existing CQA algorithm and improved channel quantization with guard-band (CQG) algorithm, simulation results show that the KDR of the proposed algorithm decreases by 31.5% and 20.4%, and the KGR decreases by 5.4% and increases by 5.2%, respectively. The proposed algorithm improves the KGR while ensuring a low KDR, and the extracted secret key passes the NIST test.

DOI
10.1109/wcsp49889.2020.9299743

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With the wide application of wireless sensor network, the security mechanism based on cryptography faces many challenges in computational complexity and security, and physical layer secret key extraction as an alternative solution has been widely studied. To meet the requirements of high key generation rate (KGR) and low key disagreement rate (KDR) in the secret key extraction process, an improved channel quantization alternating (CQA) algorithm is proposed in this paper. The algorithm filtrates the phase values of channel frequency response (CFR) using test results of CFR amplitude values, and then quantizes the reserved phase values by CQA algorithm. Compared to the existing CQA algorithm and improved channel quantization with guard-band (CQG) algorithm, simulation results show that the KDR of the proposed algorithm decreases by 31.5% and 20.4%, and the KGR decreases by 5.4% and increases by 5.2%, respectively. The proposed algorithm improves the KGR while ensuring a low KDR, and the extracted secret key passes the NIST test.
With the continuous progress of communication technology, traditional encryption algorithms cannot meet the demands of modern wireless communication security. Secure communication based on physical layer encryption emerges as a solution. To meet the low Key Disagreement Rate (KDR) and high Key Generation Rate (KGR) requirements for physical layer key generation, this paper proposes two quantization algorithms, Improve-CQG and Interpolate-CQG, based on the Channel Quantization with Guard band (CQG) algorithm. The former divides the characteristic quantization into two phases: threshold filtering and guard band quantization, while the latter adds a step after these two phases: interpolation quantization. Compared to the CQG algorithm, the Improve-CQG algorithm enhances the granularity of filtered quantization values. The core concept of the Interpolate-CQG algorithm is to utilize threshold filtering and the rounded-off quantization values from the guard band quantization phase. The symbol information corresponding to these index values is replaced by a new interpolated symbol and inserted into the key by the agreed quantized coordinates. Simulation proves that the Interpolate-CQG is an effective quantization algorithm for the key generation with lower KDR and higher KGR than the Improve-CQA and Improve-CQG.
In symmetric cryptography systems have problems in the distribution of secret keys. The two users who will communicate require sharing keys through the public channel. The proposed solution to overcome these problems is to utilize information from the physical layer (e.g. RSS). Received Signal Strength (RSS) is an indicator for measuring the power received by wireless devices. The advantage of secret key extraction using physical layer information from a wireless channel is that it allows both devices within the transmission range to extract the secret key together. In this paper, we propose a secret key generation scheme adopted from an existing scheme with modifications to improve performance. Our proposed system is applied to static and dynamic conditions to test performance. The proposed algorithm is able to obtain a reduction in KDR (Key Disagreement Rate) up to 48.42% and an increase in the KGR (Key Generation Rate) up to 23.35% when compared to the existing scheme. Our proposed system also successfully passed the randomness using the NIST test with the approximate value of entropy generated 0.80 in static conditions and 0.81 in dynamic conditions.
Exploiting the reciprocity and randomness of the wireless channel for secret key generation (SKG) is a promising technique, which attracts great interests recently toward physical layer security. Although various methods have been developed for efficient SKG, the key disagreement rate (KDR) performance is still difficult to be ensured when the transmission channel is with severe interference and noise. To alleviate this problem, this paper presents an efficient channel information extraction algorithm based on extracting effective channel paths to reduce the KDR. Simulation results demonstrate that the proposed algorithm provides significant improvement compared with the existing approaches.
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.
The Secret Key Generation (SKG) scheme that exploits the reciprocity and uniqueness of wireless channel between two users plays a significant part in a new increasing distributed security system. The scheme performance can be distinguished based on the low value of Key disagreement Rate (KDR), the high value of Key Generation Rate (KGR), as well as the fulfillment of the NIST randomness standard. The previous SKG scheme has a high KDR due to a direct quantization of a measurement result of the Received Signal Strength (RSS). To overcome the above issue, we conduct a pre-processing of measurement result before quantization with the Kalman method. The pre-process is carried out to improve the channel reciprocity between two legitimate users with the objective to reduce the bit mismatch. Through an experiment, we propose a new quantization scheme called a Modified Multi-Bit (MMB) that uses a multi-bit system on every level of quantization. The test results show that the proposed combination of preprocessing and the MMB scheme has a better performance compared to the existing schemes in terms of KDR and KGR. The Secret Key generated by our scheme also fulfills the NIST randomness standard.
As a new way to enhance wireless communication security, secret key generation based on physical layer channel characteristics has emerged. In this paper, we propose a novel secret key generation algorithm based on wireless channel characteristics for orthogonal frequency division multiplexing (OFDM) communication systems. The mean quantization algorithm is applied to quantize the real part and imaginary part of OFDM subcarriers, respectively, which can significantly increase the length of the generated secret key in the OFDM system. To reduce the consistency between the secret keys generated by the eavesdropper and the legitimate communication nodes, a processing method by taking the subcarrier phase as initialization of a scrambling code and scrambling the quantized result is proposed. The simulation and test results show that compared with the existing research, the proposed algorithm can improve the key generation rate (KGR), reduce the key mismatch rate (KMR) and complexity, maintain high randomness, and disturb the eavesdroppers.