Physical Layer Key Generation Research Articles

A powerful adversary model and corresponding OTP time slot allocation scheme in RIS-assisted physical layer key generation

Physical layer key generation (PLKG) is a technique of information-theoretic security to tackle the problem of key distribution between resource-constrained legitimate users and is a promising candidate for the one time pad (OTP) technique. However, in quasi-static, the key rate is greatly limited due to low entropy. Reconfigurable intelligent surface (RIS) is introduced to adaptively reconfigure the radio environment. However, how to allocate time slots in the OTP to counter the increasingly powerful adversary model is an urgent problem to be solved. In this paper, we propose a very powerful adversary model and give an attack strategy called eavesdropping channel search, which allows Eve to use its search and eavesdropping capabilities to maximize the probability of successful attacks. Meanwhile, we propose a time slot allocation algorithm in the OTP to ensure the security of the key. Simulations validate that our proposed attack strategy is more powerful than any existing adversary model and our proposed time slot allocation algorithm does not have any security loss.

A Breakthrough Authentication Protocol for Fortifying IoT-Cloud Security

Abstract: Physical layer key generation, leveraging the reciprocity and randomness of wireless fading channels, has garnered significant research interest in recent years. While theoretical studies have demonstrated its potential to generate informationtheoretically secure keys, challenges remain in translating theory into practice. This paper provides an overview of the physical layer key generation process and discusses its practical challenges. Various passive and active attacks are analyzed and evaluated through numerical studies. A new key generation scheme using random probing signals and combining usergenerated randomness with channel randomness is introduced to counteract active attacks. Numerical results demonstrate that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Secret-key generation relying on wireless channel reciprocity is an intriguing solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS).

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respectively. In contrast, we propose a novel secure transmission framework that combines noise entropy with reciprocity entropy, achieved by inserting reciprocity entropy into the frozen bits of polar codes. Note that in real-world scenarios, when eavesdroppers employ polynomial-time attacks, the bit error rate (BER) increases due to the introduction of computational entropy. To achieve indistinguishability security, we convert the practical physical layer security metric, BER, into the average min-entropy, a widely accepted concept in cryptography. The simulation results demonstrate that the eavesdropper’s BER can be significantly increased without compromising the communication performance of the legitimate receiver. Under concrete parameters we selected, when compared to the joint scheme of physical layer key generation and one time pad, the modular semantically-secure scheme based on the wire-tap channel model, and the simple channel entropy combination scheme, our scheme achieves a message rate approximately 1.2 times, 3.8 times, and 1.4 times better, respectively. Experimental testing validates the feasibility of our scheme.

Proficient Secret Key Generation using Derivates of the Transform Function for the Internet of Things

Secured data transfer over the internet of things enables communication devices is a very challenging task. Due to the limitation of computational resources, classical cryptography algorithms are vulnerable to cyber threats and loss of integrity and information. Recently, physical layer secret key generation has played a vital role in secured communication on the internet of things. The physical layer key generation approach provides an alternate means of information security using the signal reciprocity of wireless communication. This paper proposed proficient dynamic secret key generation using derivates of transform functions. The derivates of transform functions such as DCT, DWT, DWPT, and many more light transform functions the physical layer key generation employs RSSI channel parameters in conjunction with the discrete wavelet transform to generate low computational secret keys for the authentication of IoT-enabled communication devices. The proposed algorithm is very efficient and reduces the bit disagreement of the key. We use MATLAB software defined radios to conduct the experiment, and we then evaluate the effectiveness of our post-processing techniques. Our approach is helpful for safeguarding future IoT devices since it enhances the ability of targeted nodes to establish matching secret keys while reducing the risk of an eavesdropper. The experimental results of key generation methods suggest that the proposed algorithm is very efficient instead of DCT and DWT.

Hybrid KuFaI: A novel secure key generation algorithm using fast independent component analysis for physical layer security techniques

AbstractMany real‐world applications, such as smart cities, industrial automation, health care, and so forth, utilize IoT‐enabled devices as a part of wireless networks. IoT devices must have low power and low computation complexity requirements with proper measures of security challenges. Since traditional cryptography techniques are not computationally efficient, other alternatives, such as physical layer key generation (PLKG), is one of the attractive means to achieve security. In this paper, we propose to use a fast independent component analysis (FICA) based KuFaI (Kurtosis and FICA) algorithm for a secured PLKG system. This method reduces data dimensions and improves system performance regarding Bit Disagreement Rate (BDR) and randomness. In KuFaI, we rearrange the received signal strength indicator (RSSI) data set using FICA and then select components based on the kurtosis function. Results demonstrate that the performance of the proposed algorithm is far better than the previously used PCA‐based algorithm.

Artificial intelligence empowered physical layer security for 6G: State-of-the-art, challenges, and opportunities

With the commercial deployment of the 5G system, researchers from both academia and industry are moving attention to the blueprint of the 6G system. The space–air–ground–sea integrated 6G system is envisioned to support various new applications with very diverse requirements in terms of quality of service and security. Due to the open nature of the wireless channel, highly dynamic network topology, and mission-critical applications, 6G will face various security threats. The conventional upper-layer cryptography-based security mechanisms face multiple challenges to resist physical layer attacks in the context of large numbers computing, power-limited low-cost Internet of Thing (IoT) devices. The Physical layer security (PLS) mechanisms by exploiting the random nature of the wireless channel and intrinsic hardware imperfection provide complementary approaches to secure the 6G system. Meanwhile, the quick development and successful application of artificial intelligence facilitate the advancement of PLS solutions. In this paper, we make a comprehensive overview of machine learning-empowered PLS techniques toward 6G. We first introduce the vision of the 6G system, typical applications, key enabling radio technologies, security threats, and security requirements to 6G. Then typical machine learning (ML) methods and the driving forces for introducing intelligent PLS in 6G are presented. Afterward, the major academic works on PLS oriented to key 6G radio techniques including cell-free massive MIMO, visible light communication, Terahertz technology, configurable intelligent surfaces, molecular communication, and ambient backscatter communication are discussed. Then, the latest works on ML-enabled PLS solutions including physical layer key generation, secure wireless transmission, physical layer authentication, intelligent anti-jamming, and ML-enabled attack and detection are systematically reviewed. Finally, we identify important open issues and future research opportunities to inspire further studies to realize a more intelligent and secure 6G system.

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 Countermeasure Against RIS Jamming Attack in Physical-Layer Key Generation

A Countermeasure Against RIS Jamming Attack in Physical-Layer Key Generation

RIS-Aided Physical Layer Key Generation of IoT Network in Static Environments (March 2023)

RIS-Aided Physical Layer Key Generation of IoT Network in Static Environments (March 2023)

Ensuring Privacy in Wireless Channels with Physical Layer Security: A Survey of Encryption Strategies

This paper reviews various encryption strategies designed to enhance privacy in wireless communication, with a focus on leveraging physical layer security. Exploring techniques that utilize inherent wireless channel features for secure communication, the survey presents the strengths and challenges of each method. The aim is to provide a straightforward overview for researchers, practitioners, and decision-makers, about the evolving landscape of encryption methods in wireless channels for improved privacy. Furthermore, it discusses how these physical layer key generation techniques can be integrated with advanced technologies by providing a suggested model by combining the Machine learning and the Multi authority ciphertext-policy attribute-based encryption (CP-ABE) to ensure privacy in wireless channels.

A Novel Hybrid Protocol and Code Related Information Reconciliation Scheme for Physical Layer Secret Key Generation

Wireless networks are vulnerable to various attacks due to their open nature, making them susceptible to eavesdropping and other security threats. Eavesdropping attack takes place at the physical layer. Traditional wireless network security relies on cryptographic techniques to secure data transmissions. However, these techniques may not be suitable for all scenarios, especially in resource-constrained environments such as wireless sensor networks and adhoc networks. In these networks having limited power resources, generating cryptographic keys between mobile entities can be challenging. Also, the cryptographic keys are computationally complex and require key management infrastructure. Physical Layer Key Generation (PLKG) is an emerging solution to address these challenges. It establishes secure communication between two users by taking advantage of the wireless channel's inherent features. PLKG process involves channel probing, quantization, information reconciliation (IR) and privacy amplification to generate symmetric secret key. The researchers have used various PLKG techniques to get the secret key, sTop of Form
 till they face problems in the IR scheme to obtain symmetric keys between the users who share the same channel for communication. Both the code based and protocol based methods proposed in the literature have advantages and limitations related to their performance parameters such as information leakage, interaction delay and computation complexity. This research work proposes a novel IR mechanism that combines the protocol and code-based error correction methods to obtain reduced Bit Mismatch Rate (BMR), reduced information leakage, reduced interaction delay, and reduced computational time to enhance physical layer secret key's quality. In the proposed research work, the channel samples are generated using the Received Signal Strength (RSS) and Channel Impulse Response (CIR) parameters. These samples are quantized using Vector Quantization with Affinity Propagation Clustering (VQAPC) method to generate the preliminary key. The samples collected by the two users who wish to communicate, (for example Alice and Bob) will be different due to noise in the channel and hardware limitations. Hence their preliminary keys will be different. Removing this discrepancy between Bob's and Alice's initial keys, using novel Hybrid Protocol and Code related Information Reconciliation (HPC-IR) scheme to generate error corrected key, is the most important contribution of this research work. This key is further encoded by the MD5 hash function to generate a final secret key for exchanging information between two users over the wireless channel. It is observed that the proposed HPC-IR scheme achieves BMR of 19.4%, information leakage is 0.002, interaction delay is 0.001 seconds and computation time is 0.02 seconds.

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

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

Securing NextG networks with physical-layer key generation: A survey

As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks.

Security Provided by the Physical Layer in Wireless Communications

This article provides an overview of five physicallayer security mechanisms: Physical-Layer Authentication (PLA), Physical-Layer Confidential Communications (PLCC), Physical- Layer Key Generation (PLKG), Physical-Layer Communications with Low Probability of Detection (PLC-LPD), and Physical- Layer Steganography (PLS). We explain the relationship among five physical-layer security mechanisms. Then, we review the features of various physical-layer security mechanisms in terms of the basic idea, properties, assumptions, classification, threat model, and applications, respectively. At last, we introduce five promising plans by combining different physical-layer security mechanisms to further improve the final performance.

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.

Random Beam Switching: A Physical Layer Key Generation Approach to Safeguard mmWave Electronic Devices

Extracting secret keys from millimeter wave (mmWave) wireless channels fast and efficiently for securing communications between mmWave electronic devices is a challenge due to the limitations of static environments. In this paper, we propose a random beam switching (RBS) based physical layer key generation (PLKG) scheme in the mmWave systems. Utilizing the sparsity characteristics of mmWave channels between electronic devices, we apply virtual angles of effective-beams and activated-beams as the random source. Through channel detection, we establish an RBS space between the transmitter and receiver. Then they randomly select beams from the RBS space and transmit reference signals to generate consistent keys. Furthermore, by using information theory, we analyze the effectiveness, reliability and security performance of RBS scheme theoretically. Specifically, we derive the theoretical expression of key generation rate (KGR) and then obtain its upper bound. We also prove that the key mismatch ratio (KMR) approaches zero in the high signal-to-noise ratio (SNR) region. Then we demonstrate that the eavesdropper cannot obtain any information about the activated-beams. Numerical results are provided to verify our theoretical analysis. We demonstrate that the RBS scheme can provide sufficient secret keys even in static environments while achieving good secrecy performance to safeguard electronic devices.

Lightweight and Fast Physical-Layer Key Generation in FDD Systems using Random Forest

Physical-layer Secure Key Generation (SKG) in wireless communication provides high-level security originating from channel uniqueness. However, the carrier frequency difference in Frequency Division Duplexing (FDD) systems degrades the channel reciprocity, compromising the feasibility of SKG and subsequently the Key Generation Rate (KGR). We propose a lightweight and fast SKG scheme with enhanced KGR in FDD systems, using the Random Forest (RF) algorithm in conjunction with a Multi-to-Single Mapping (M2SM) strategy. Besides, the Moving Average (MA) and subtraction algorithms further enhance the SKG performances under noisy and frequency-selective fading FDD channels. Experimental results revealed an error-free KGR of 57.71 Kbps, with superior randomness, showing the practicability of high-speed and robust SKG in FDD systems. Moreover, the proposed scheme has low complexity, high flexibility, and information-theoretic security.

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.

Physical-layer key generation based on multipath channel diversity using dynamic metasurface antennas

Physical layer key generation (PKG) technology leverages the reciprocal channel randomness to generate the shared secret keys. The low secret key capacity of the existing PKG schemes is due to the reduction in degree-of-freedom from multipath fading channels to multipath combined channels. To improve the wireless key generation rate, we propose a multipath channel diversity-based PKG scheme. Assisted by dynamic metasurface antennas (DMA), a two-stage multipath channel parameter estimation algorithm is proposed to efficiently realize super-resolution multi-path parameter estimation. The proposed algorithm first estimates the angle of arrival (AOA) based on the reconfigurable radiation pattern of DMA, and then utilizes the results to design the training beamforming and receive beamforming to improve the estimation accuracy of the path gain. After multipath separation and parameter estimation, multi-dimensional independent path gains are utilized for generating secret keys. Finally, we analyze the security and complexity of the proposed scheme and give an upper bound on the secret key capacity in the high signal-to-noise ratio (SNR) region. The simulation results demonstrate that the proposed scheme can greatly improve the secret key capacity compared with the existing schemes.