The diverse application scenarios envisioned for sixth generation (6G) are characterized by the deep integration of sensing and ubiquitous connectivity, which imposes unprecedentedly stringent security requirements. However, due to the open nature of wireless channels, mobile communications systems always face severe information security threats such as falsification, spoofing, interception, and repudiation. Cryptography-based symmetric and asymmetric encryption techniques remain mainstream solutions for information protection. Symmetric encryption is efficient and secure for legitimate users but suffers from key-distribution difficulties over open wireless channels, whereas asymmetric encryption resolves this problem but faces increasing risks from quantum computing due to its reliance on structured mathematical hardness assumptions. In response to these limitations, physical layer security (PLS) has gained a great deal of research attention as a powerful security component that leverages the features of varying wireless channels. Existing PLS schemes can be broadly classified into two categories. The first one takes advantage of the legitimate link’s opportunistic channel-quality superiority over or different spatial-domain directions from the attacking link, which still faces many practical implementation difficulties. The second category is termed physical-layer key generation (PLKG). It extracts the unique features of the legitimate link’s channel variation, which is often reciprocal, as the source of secret key generation and therefore can naturally implement secure key distribution tasks. This advantage no doubt injects new vigor to symmetric encryption as a stronger protection approach. Following this trend, we in this paper concentrate on the PLKG techniques. Specifically, we present a comprehensive overview on existing PLKG schemes, discussing diverse secret key generation and reconciliation methods. We further investigate the model-driven and deep-learning-based approaches tailored for the scenario with imperfect channel reciprocity between the sender and receiver. After comprehensively reviewing major existing schemes, we further discuss a recently proposed PLKG design based on codeword reconstruction, which makes use of the strong error-correcting capability of the forward-error-correction (FEC) codes to effectively implement secure and consistent secret key generation between the legitimate sender and receiver. Finally, we share our opinions on the unsolved challenges and potential research directions dedicated to PLKG toward meeting the security requirements of 6G.
The diverse application scenarios envisioned for sixth generation (6G) are characterized by the deep integration of sensing and ubiquitous connectivity, which imposes unprecedentedly stringent security requirements. However, due to the open nature of wireless channels, mobile communications systems always face severe information security threats such as falsification, spoofing, interception, and repudiation. Cryptography-based symmetric and asymmetric encryption techniques remain mainstream solutions for information protection. Symmetric encryption is efficient and secure for legitimate users but suffers from key-distribution difficulties over open wireless channels, whereas asymmetric encryption resolves this problem but faces increasing risks from quantum computing due to its reliance on structured mathematical hardness assumptions. In response to these limitations, physical layer security (PLS) has gained a great deal of research attention as a powerful security component that leverages the features of varying wireless channels. Existing PLS schemes can be broadly classified into two categories. The first one takes advantage of the legitimate link’s opportunistic channel-quality superiority over or different spatial-domain directions from the attacking link, which still faces many practical implementation difficulties. The second category is termed physical-layer key generation (PLKG). It extracts the unique features of the legitimate link’s channel variation, which is often reciprocal, as the source of secret key generation and therefore can naturally implement secure key distribution tasks. This advantage no doubt injects new vigor to symmetric encryption as a stronger protection approach. Following this trend, we in this paper concentrate on the PLKG techniques. Specifically, we present a comprehensive overview on existing PLKG schemes, discussing diverse secret key generation and reconciliation methods. We further investigate the model-driven and deep-learning-based approaches tailored for the scenario with imperfect channel reciprocity between the sender and receiver. After comprehensively reviewing major existing schemes, we further discuss a recently proposed PLKG design based on codeword reconstruction, which makes use of the strong error-correcting capability of the forward-error-correction (FEC) codes to effectively implement secure and consistent secret key generation between the legitimate sender and receiver. Finally, we share our opinions on the unsolved challenges and potential research directions dedicated to PLKG toward meeting the security requirements of 6G.
With the burgeoning internet of things (IoT), securing communication becomes paramount. Traditional cryptography does not meet computational needs and brute-force attacks. This review explores the state-of-the-art physical layer secret key generation (PLKG) that takes advantage of the inherent reciprocity and randomness of wireless channels. We investigate cutting-edge techniques such as feature extraction networks, domain adversarial training, and deep learning-based approaches, evaluating their effects on the security and efficiency of key generation. In addition to these methods, the review addresses real-world challenges such as multi-user scenarios, reconciliation overhead, and inconsistent channel measurement. We believe that improved key generation rates and security can be achieved through the use of millimeter wave technology and full-duplex communication. To strengthen the robustness of key generation, the paper concludes by suggesting future directions, such as incorporating more random sources, such as physiological signals and sensor data. This comprehensive overview offers deep insights into the state-of-the-art and paves the way for reliable communication in ever more complicated IoT settings.
The open nature of radio propagation enables ubiquitous wireless communication. This allows for seamless data transmission. However, unauthorized users may pose a threat to the security of the data being transmitted to authorized users. This gives rise to network vulnerabilities such as hacking, eavesdropping, and jamming of the transmitted information. Physical layer security (PLS) has been identified as one of the promising security approaches to safeguard the transmission from eavesdroppers in a wireless network. It is an alternative to the computationally demanding and complex cryptographic algorithms and techniques. PLS has continually received exponential research interest owing to the possibility of exploiting the characteristics of the wireless channel. One of the main characteristics includes the random nature of the transmission channel. The aforesaid nature makes it possible for confidential and authentic signal transmission between the sender and the receiver in the physical layer. We start by introducing the basic theories of PLS, including the wiretap channel, information-theoretic security, and a brief discussion of the cryptography security technique. Furthermore, an overview of multiple-input multiple-output (MIMO) communication is provided. The main focus of our review is based on the existing key-less PLS optimization techniques, their limitations, and challenges. The paper also looks into the promising key research areas in addressing these shortfalls. Lastly, a comprehensive overview of some of the recent PLS research in 5G and 6G technologies of wireless communication networks is provided.
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.
In recent years, physical layer security has become one of the core technologies for wireless communication system security. Physical layer encryption is based on the inherent reciprocity, time-varying, spatial uniqueness and unpredictability of wireless communication systems to generate keys, which are naturally unforgeable and steganography-proof. However, the research of physical layer key generation technology also faces many challenges, such as the problem of poor key generation performance due to signal interference, the problem of lower randomness and slower key generation rate in quasi-static channel environment, and the problem of lower key consistency between two legitimate communication parties due to the existence of channel estimation errors; this paper provides a systematic explanation of the traditional model of key generation for wireless channels and a typical solution for this series of problems. In this paper, the traditional model of wireless channel key generation is systematically explained, and the typical solutions to this series of problems are studied, analysed and compared in terms of performance.
Physical Layer Key Generation (PKG) has evolved as a promising technique to circumvent the problems faced by the classical symmetric key production schemes. It exploits channel reciprocity and spatial decorrelation provided by wireless medium. This paper systematically reviews the evolution of PKG technologies, discussing their working principles, performance metrics, and implementations under various scenarios such as slow-fading channels, low SNR, and multi-user environments. With recent advancements introduced—intelligent reflecting surfaces (RIS/STAR-RIS), optimization powered by AI/ML, and their integration with massive MIMO and terahertz communications—chaos, robustness, and scalability enhancements are investigated. Further exploration involves application domains from IoT and healthcare to Industry 4.0 and 6G networks, this focus shifting from proof of feasibility to full-fledged implementation. The concluded findings show that PKG is inclined to become a key security primitive for next-generation wireless systems to enjoin lightweight and efficient friendly key management schemes.
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.