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.
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.
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.
Wireless communication systems are becoming increasingly important in our daily lives, especially with the rapid expansion of the Internet of Things (IoT). Secure and reliable communication is essential for the correct functioning of critical applications and use cases such as healthcare, finance, transportation, and industrial automation. However, the growing number of connected devices introduces significant challenges to data security and privacy due to the open nature of wireless networks. While traditional encryption methods are effective, they can be resource-intensive and impractical for resource-constrained IoT environments. Physical layer security (PLS) provides a lightweight alternative by leveraging the inherent characteristics of wireless channels to generate symmetric secret keys without requiring third-party infrastructure. The PLS key generation process involves four main stages: channel sampling, quantization, reconciliation, and privacy amplification. This paper provides a comprehensive survey of existing quantization schemes, as this step plays a crucial role in determining the key generation rate (KGR) and key disagreement rate (KDR). Additionally, the paper classifies quantization methods as either lossless or lossy, providing insights into the trade-offs between security and efficiency.
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.
This paper introduces a novel physical layer secure communication technology based on wireless channel direct encryption to enhance the encryption strength of the information source. Unlike traditional methods of key generation based on the reciprocity of the wireless channel, which typically involve quantizing the wireless channel and then negotiating keys, resulting in two completely identical bit strings generated as encryption keys for upper-level cryptographic algorithms between legitimate communication parties, this paper's approach quantizes the quantized bits of the wireless channel characteristics of both legitimate parties and directly encrypts the information source bits by using a designed lightweight encryption/decryption algorithm. Compared to traditional approaches, this paper's method avoids the key consultation process for physical layer key distribution, expanding the scenarios for the use of physical layer keys. Moreover, it can work independently at the same time with the upper layer cryptography to enhance the encryption strength. Through experimental verification, it has been confirmed that, in cases where the channel error rate during information transmission is less than 5*10^-2, this model can achieve an average reception accuracy of 99.6% for legitimate communicators while ensuring that eavesdroppers cannot decrypt. This approach can also compatible with upper-layer security encryption/decryption algorithms at each layer of the OSI, e.g., data link layer and network layer, offering extensive application prospects.
With the development of wireless communication technology, the application of the physical layer key generation method based on channel characteristics is becoming more and more widespread. In this method, the selection of quantization algorithm in the quantization stage is particularly important. The poor performance of the initial key will affect the efficiency of key reconciliation, and even cause the failure of the whole key generation method. In the existing quantization algorithms, the quantization level and guard interval are fixed, so the performance of the initial key cannot always be optimized in the face of complex and changeable communication environment. Aiming at the above problems, this paper combines the adaptive adjustment of quantization level and guard interval effectively on the basis of existing multi-bit quantization algorithm. This method continues the method of deleting eigenvalues by index value in multi-bit quantization algorithm, which improves the consistency of initial key. Based on information theory, this method selects optimal quantization level on the premise that the initial key is theoretically error-free under different SNR. This method sets the guard interval based on the average error probability of the eigenvalue and the quantization level, which solves the problem of deleting too many eigenvalues when the SNR is high in the method of setting fixed guard interval. Simulation results show that this method is feasible.
Wireless channel key generation technology is an important mechanism to guarantee the security of wireless network, but influenced by the key length and the actual electromagnetic environment, wireless channel key generation technology is faced with the challenge of high-key generation rate (KGR) and low-key disagreement rate (KDR). The existing key generation methods also lack the full use of the channel state information (CSI). We propose a key generation method based on multisubcarrier phase difference to expand the randomness source dimension, eliminate the phase bias, offset part of the noise influence, and set the threshold screening data to reduce the influence of measurement error. We further propose a key generation method based on resampling of kernel density estimation (KDE), which yields highly reciprocal randomness sources by resampling the results of KDE of phase difference values. To fill the metric gap of whether a method keeps low KDR while increasing the KGR, the evaluation metric of effective improvement ratio (EIR) is proposed. The two methods we proposed have a higher EIR than the method of using multiple-input and multiple-output (MIMO) and increasing the quantization level, achieving the goal of increasing the KGR while maintaining the low KDR. The KGR can reach about 12146 bits/s, and the KDR is 1.83%. The keys obtained by both methods can effectively prevent passive eavesdropping and meet the randomness requirements.