Physical Layer Key Generation Scheme Research Articles

A Reliable Physical Layer Key Generation Scheme Based on RSS and LSTM Network in VANET

With the rapid development of information and communication technology, Vehicular AD hoc Networks (VANET) has attracted more and more attention. In order to provide traffic safety services, vehicles frequently share information related to road traffic, such as vehicle motion data and traffic flow data. Reliable key generation is the basis of VANET security system construction. At present, most key generation schemes rely on a trusted third-party, so there are security risks. Traditional key agreement protocols have high overhead, and is not suitable for the latency-sensitive requirements of VANET. The physical layer security technology extracts the fingerprint of the wireless channel and the identity of the device, and generates the key quickly and in real time without the third party distribution. A physical layer key generation scheme based on Received Signal Strength (RSS) is proposed to realize Vehicle-to-Vehicle (V2V) secure communications. Firstly, a network model based on Long Short-Term Memory (LSTM) network and Kalman Filtering is proposed to effectively enhance the reciprocity of physical layer information in dynamic environment. Secondly, a lossless quantization scheme is proposed, which achieves a lower bit disagreement rate and a higher bit generation rate. Thirdly, the inconsistent bits are corrected by fuzzy extractor, the confidentiality of the key exchange process is enhanced by zero knowledge proof, and the security of the key is improved by using hash function for privacy amplification. Finally, the experimental results show that the proposed scheme has great improvements in data correlation, bit disagreement rate, bit generation rate and bit distribution randomness.

A Highly Consistent and High-speed Physical Layer Key Generation Scheme

A Highly Consistent and High-speed Physical Layer Key Generation Scheme

Physical Layer Key Generation Scheme for MIMO System Based on Feature Fusion Autoencoder

Recently, the use of wireless channel state information (CSI) to generate encryption keys in the physical layer has gained significant attention from researchers. Unlike classical cryptography, this approach relies on the variability of the wireless channel, channel reciprocity, and spatial decorrelation to ensure security, making it more lightweight and providing strong randomness. This paper proposes a physical layer key generation scheme for wireless LAN MIMO systems based on feature fusion autoencoder (FFAEncoder) to address the issue of a high key disagreement rate (KDR). Our approach involves extracting amplitude and phase features separately, fusing them through multiplication operator in a neural network, and using an autoencoder to extract common features. The proposed scheme was evaluated on multiple datasets in different real-world scenarios, and it was found that the transmitter and receiver codeword’s mean squared error (MSE) and mean absolute error (MAE) were smaller than those of the current models, indicating better key generation performance. Additionally, the proposed scheme’s KDR was smaller, with a decay rate faster than that of the other two models in the same environment, and the primary key bits were 1/2 and 1/3 that of the other models, respectively, as the signal-to-noise ratio (SNR) increased.

An anti-collusion attack defense method for physical layer key generation scheme based on transmission delay.

Physical layer security (PLS) is considered one of the most promising solutions to solve the security problems of massive Internet of Things (IoTs) devices because of its lightweight and high efficiency. Significantly, the recent physical layer key generation (PLKG) scheme based on transmission delay proposed by Huang et al. (2021) does not have any restrictions on communication methods and can extend the traditional physical layer security based on wireless channels to the whole Internet scene. However, the secret-sharing strategy adopted in this scheme has hidden dangers of collusion attack, which may lead to security problems such as information tampering and privacy disclosure. By establishing a probability model, this article quantitatively analyzes the relationship between the number of malicious collusion nodes and the probability of key exposure, which proves the existence of this security problem. In order to solve the problem of collusion attack in Huang et al.'s scheme, this article proposes an anti-collusion attack defense method, which minimizes the influence of collusion attack on key security by optimizing parameters including the number of the middle forwarding nodes, the random forwarding times, the time delay measurement times and the out-of-control rate of forwarding nodes. Finally, based on the game model, we prove that the defense method proposed in this article can reduce the risk of key leakage to zero under the scenario of the "Careless Defender" and "Cautious Defender" respectively.

A Physical Layer Key Generation Scheme Based on Deep Learning Compensation and Balanced Vector Quantization

Channel reciprocity is the foundation for physical layer key generation, which is influenced by noise, hardware impairments, and synchronization offsets. Weak channel reciprocity will result in a high key disagreement rate (KDR). The existing solutions for improving channel reciprocity cannot achieve satisfactory performance improvements. Furthermore, the existing quantization algorithms generally use one-dimensional channel features to quantize and generate secret keys, which cannot fully utilize channel information. The multidimensional vector quantization technique also needs to improve in terms of randomness and time complexity. This paper proposes a physical layer key generation scheme based on deep learning and balanced vector quantization. Specifically, we build a channel reciprocity compensation network (CRCNet) to learn the mapping relationship between Alice and Bob’s channel measurements. Alice compensates for channel measurements via a trained CRCNet to reduce channel measurement errors between legitimate users and enhance channel reciprocity. We also propose a balanced vector quantization algorithm based on integer linear programming (ILP-BVQ). ILP-BVQ reduces the time complexity of quantization on the basis of ensuring key randomness and a low KDR. Simulation results showed that the proposed CRCNet performs better in terms of channel reciprocity and KDR, while the proposed ILP-BVQ algorithm improves time consumption and key randomness.

Security Analysis of Triangle Channel-Based Physical Layer Key Generation in Wireless Backscatter Communications

Ambient backscatter communication (AmBC) enables ultra-low-power communications by backscattering ambient radio frequency (RF) signals and harvesting energy simultaneously. It has emerged as a cutting-edge technology for supporting a variety of Internet of Things (IoT) applications. However, existing research lacks effective secret key sharing schemes for safeguarding communications between resource-constrained backscatter devices (BDs) in AmBC systems. In this paper, we present, Tri-Channel, a novel physical layer key generation scheme between two BDs by multiplying downlink signals and backscatter signals to obtain the information of a triangle channel as a shared random secret source for key generation. In particular, we analyze the security of our scheme under both passive and active attacks, concretely Eavesdropping Attack (EA), Control Channel Attack (CCA), Signal Manipulative Attack (SMA), and Untrusted RF-Source Attack (URSA). Through theoretical analysis and simulations by comparing with a traditional scheme (named Tradi-Channel), we found that our scheme consistently outperforms the Tradi-Channel under the EA and two active attacks (CCA and SMA). In addition, it shows better security performance under URSA, which is proposed based on the unauthenticated characteristic of BDs in Tri-Channel, even though URSA is more vital than SMA. Concretely, Tri-Channel’s secret key rate (SKR) outperforms Tradi-Channel’s under the above four passive and active attacks. This implies that our scheme is advanced in terms of both security and efficiency of key generation. Numerous extensive simulations further prove our theoretical analysis results.

Physical-Layer-Based Secure Communications for Static and Low-Latency Industrial Internet of Things

This article proposes a wireless key generation solution for secure low-latency communications with active jamming attack prevention in wireless networked control systems (WNCSs) of Industrial Internet of Things (IIoT) applications. We first identify a new vulnerability in physical-layer key generation schemes using wireless channel and random pilots (RPs) in static environments. We derive a closed-form expression for the probability that the RP-based key is successfully attacked by a long-term eavesdropper at a fixed location. To prevent such attacks, we propose a one-time pad (OTP) encrypted transmission solution assisted by one-way self-interference (SI), which has low-latency, high-security benefits, and active attack detection capability. The performance of the proposed scheme is analytically compared with two benchmark RP-based schemes, and its advantages are verified in a ray-tracing-based simulation environment. We further investigate the impact of critical design parameters, which reveal fundamental insights for the deployment and implementation of our proposed secure communications scheme.

Reconfigurable Intelligent Surface for Physical Layer Key Generation: Constructive or Destructive?

Physical layer key generation (PKG) is a promising means to provide on-the-fly shared secret keys by exploiting the intrinsic randomness of the radio channel. However, the performance of PKG is highly dependent on the propagation environments. Due to its feature of controlling the wireless environment, reconfigurable intelligent surface (RIS) is appealing to be applied in PKG. In this article, in contrast to the existing literature, we investigate both the constructive and destructive effects of RIS on the PKG scheme. For the constructive aspect, we have identified static and wave-blockage environments as two RIS-empowered-PKG applications in future wireless systems. In particular, our experimental results in a static environment showed that RIS can enhance the entropy of the secret key, achieving a key generation rate (KGR) of 97.39 bit/s with a bit disagreement rate (BDR) of 0.083. In multi-user systems where some remote users are in worse channel conditions, the proposed RIS-assisted PKG algorithm improves the sum secret key rate by more than 2 dB, compared to the literature. Furthermore, we point out that RIS could be utilized by an attacker to perform new jamming and leakage attacks and give countermeasures, respectively. Finally, we outline future research directions for PKG systems in light of the RIS.

Deep-Learning-Based Physical-Layer Secret Key Generation for FDD Systems

Physical-layer key generation (PKG) establishes cryptographic keys from highly correlated measurements of wireless channels, which relies on reciprocal channel characteristics between uplink and downlink, is a promising wireless security technique for Internet of Things (IoT). However, it is challenging to extract common features in frequency-division duplexing (FDD) systems as uplink and downlink transmissions operate at different frequency bands whose channel frequency responses are not reciprocal anymore. Existing PKG methods for FDD systems have many limitations, i.e., high overhead and security problems. This article proposes a novel PKG scheme that uses the feature mapping function between different frequency bands obtained by deep learning to make two users generate highly similar channel features in FDD systems. In particular, this is the first time to apply deep learning for PKG in FDD systems. We first prove the existence of the band feature mapping function for a given environment and a feedforward network with a single hidden layer can approximate the mapping function. Then, a key generation neural network (KGNet) is proposed for reciprocal channel feature construction, and a key generation scheme based on the KGNet is also proposed. Numerical results verify the excellent performance of the KGNet-based key generation scheme in terms of randomness, key generation ratio, and key error rate. Besides, the overhead analysis shows that the method proposed in this article can be used for resource-constrained IoT devices in FDD systems.

Intelligent Reflecting Surface-Assisted Wireless Secret Key Generation against Multiple Eavesdroppers.

In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user’s SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex–concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.

LoRa-Based Physical Layer Key Generation for Secure V2V/V2I Communications.

In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have not been fully addressed in V2V and V2I systems, especially in key distribution and key management. The physical layer key generation, which exploits wireless channel reciprocity and randomness to generate secure keys, provides a feasible solution for secure V2V/V2I communication. It is lightweight, flexible, and dynamic. In this paper, the physical layer key generation is brought to the V2I and V2V scenarios. A LoRa-based physical key generation scheme is designed for securing V2V/V2I communications. The communication is based on Long Range (LoRa) protocol, which is able to measure Received Signal Strength Indicator (RSSI) in long-distance as consensus information to generate secure keys. The multi-bit quantization algorithm, with an improved Cascade key agreement protocol, generates secure binary bit keys. The proposed schemes improved the key generation rate, as well as to avoid information leakage during transmission. The proposed physical layer key generation scheme was implemented in a V2V/V2I network system prototype. The extensive experiments in V2I and V2V environments evaluate the efficiency of the proposed key generation scheme. The experiments in real outdoor environments have been conducted. Its key generation rate could exceed 10 bit/s on our V2V/V2I network system prototype and achieve 20 bit/s in some of our experiments. For binary key sequences, all of them pass the suite of statistical tests from National Institute of Standards and Technology (NIST).

Efficient physical layer key generation technique in wireless communications

Wireless communications between two devices can be protected by secret keys. However, existing key generation schemes suffer from the high bit disagreement rate and low bit generation rate. In this paper, we propose an efficient physical layer key generation scheme by exploring the Received Signal Strength (RSS) of signals. In order to reduce the high mismatch rate of the measurements and to increase the key generation rate, a pair of transmitter and receiver separately apply adaptive quantization algorithm for quantifying the measurements. Then, we implement a randomness extractor to further increase key generation rate and ensure randomness of generated of keys. Several real-world experiments are implemented to verify the effectiveness of the proposed scheme. The results show that compared with the other related schemes, our scheme performs better in bit generation rate, bit disagreement rate, and randomness.

Physical Layer Key Generation Scheme Through Scrambling the Correlated Eavesdropping Channel

In this paper, we investigate the physical layer key generation scheme in most realistic scenarios where the correlation between the legitimate channel and the eavesdropping channel is considered. To degrade the correlation and improve the key generation capacity, a physical layer key generation scheme through scrambling the correlated eavesdropping channel is proposed. Firstly, the artificial noise is sent superimposed over pilots from the legitimate transmitter to confuse the eavesdropper. The artificial noise precoding matrix is randomly selected from decomposed unitary matrices orthogonal to the legitimate channel resulting in having no effect on legitimate channel. Then, the vector quantization algorithm and the winnow algorithm are respectively applied to quantize the channel characteristic and negotiate the generated random sequences to generate the final key. To further support the performance, we next present a power optimization scheme allocated to sending the artificial noise to maximize the generated key capacity under the total transmission power constraint. Finally, simulation results are presented to validate the effectiveness of our proposed scheme.

基于EMD的物理层生成密钥方案在车辆通信中的研究

基于EMD的物理层生成密钥方案在车辆通信中的研究

Physical Layer Key Generation in 5G Wireless Networks

The bloom of 5G communication and beyond serves as a catalyst for physical layer key generation techniques. In 5G communications systems, many challenges in traditional physical layer key generation schemes, such as co-located eavesdroppers, the high bit disagreement ratio, and high temporal correlation, could be overcome. This article lists the key enabling techniques in 5G wireless networks, which offer opportunities to address existing issues in physical layer key generation. We survey the existing key generation methods and introduce possible solutions for the existing issues. The new solutions include applying the high signal directionality in beamforming to resist co-located eavesdroppers, utilizing the sparsity of millimeter-wave channel to achieve a low bit disagreement ratio under low signal-to-noise ratio, and exploiting hybrid precoding to reduce the temporal correlation among measured samples. Finally, the future trends of physical layer key generation in 5G and beyond communications are discussed.

A key generation scheme for wireless physical layer based on frequency hopping

Wireless physical layer key generation technology can effectively solve the problem of key distribution and management in traditional security mechanisms, and thus has been widely studied. In this paper, we propose a physical layer key generation scheme based on frequency hopping, which improves the key generation efficiency under the condition of static wireless channel with low physical layer key generation efficiency and low randomness. In addition, we apply the moving average and principal component analysis (PCA) of preprocessing methods to the channel characteristics, and perform double-threshold quantization to improve the consistency of the key generation. Finally, we verify the proposed key generation scheme on the hardware platform consisting of STM8L101 and CC1101. The experimental results show that when the frequency hopping step is 200KHz, the key agreement rate is higher than 99% and the key generation efficiency is 88%.