Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Transactions on Information Forensics and Security

A High-Entropy Physical Layer Key Generation Scheme for 5G Systems

Shichang Guo, Yuanyu Zhang, Jiayi Guo, Shuangrui Zhao, Ji He, Yulong Shen, Xiaohong Jiang

Published Jan 1, 2025• 4 citations
Publisher

Abstract

The fifth-generation mobile communication technology (5G) supports wireless data transmission across civil, commercial, industrial, and even military networks, where vast amounts of privacy data are constantly transmitted. However, the open nature of the air interface in 5G systems makes them vulnerable to various attacks. Physical-layer key generation (PKG) has been recognized as a highly promising technology for ensuring data security in 5G systems, while existing PKG schemes achieve low key entropy (i.e., low key randomness) due to poor channel probing and quantization. In this paper, we propose a PKG scheme with high key entropy, tailored to the unique characteristics of 5G systems. First, we design a channel probing method based on the demodulation reference signal in accordance with 5G standards, enhancing the similarity between channel measurements. Next, we introduce a quantization method based on local increment and monotonicity, which effectively leverages channel characteristics to achieve high-speed key generation and improve key entropy. Finally, we use both MATLAB simulation and real-world channel measurements to achieve comprehensive verification of the proposed scheme. The simulation results showed that the proposed scheme increases the key entropy by at least 25% with nearly the same key generation rate compared with existing PKG schemes for 5G systems. The experiment using real-world channel measurements also confirmed that the proposed scheme has higher key entropy.

DOI
10.1109/tifs.2025.3588684

Related papers

A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks

Qiuhua Wang, Mingyang KANG, Guohua Wu +2 more

Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.

IEICE Transactions on Information and Systems•Jan 31, 2020•7 citations

Physical Layer Key Generation for 5G: Leveraging Dm-Rs Channel Estimation and Ldpc Soft-Decision Quantization for Key Reconciliation

Hongyu Ye, Dengke Guo, Dongtang Ma +1 more

Physical layer key generation (PLKG) offers a lightweight and low-complexity key management solution for future emerging wireless communication networks. However, current PLKG schemes face challenges in effective integration with practical communication systems, hindering their practical deployment. To solve this problem, this paper proposes a key generation scheme integrated with the 5 G physical layer protocol, leveraging the Demodulation Reference Signal (DM-RS) to extract channel estimation for PLKG, enabling efficient key generation. Furthermore, a soft-decision quantization method based on Multibit Adaptive Quantization is proposed which makes key reconciliation input compatible with the soft-decision input requirements of the Low-Density Parity-Check (LDPC) decoder in 5G channel coding module. Simulation results demonstrate that the proposed scheme successfully integrates into the 5G standard communication framework while still maintaining favorable key disagreement rate (KDR) performance, the key reconciliation using keys derived by soft-decision quantization method can achieve better key agreement performance than using keys derived by binary quantization.

International Conference on Intelligent Communications and Computing (ICICC)•Aug 15, 2025•0 citations

A 5G Physical Layer Key Generation Scheme Based on Attention-Integrated Autoencoder

Weicheng Zhang, Liquan Chen, Tianyu Lu +3 more

The fifth generation ($\mathbf{5 G}$) communication is progressively being commercialized and civilianized. It is crucial to protect the wireless transmission of sensitive information. Physical layer key generation (PLKG) emerges as a lightweight symmetric key generation technique based on channel reciprocity, which can further ensure the security of 5 G communications. Aiming at the problem of weak channel reciprocity in 5 G communications, this paper proposes a 5G PLKG scheme based on an attention-integrated autoencoder. Firstly, channel probing time slots are planned in accordance with the slot configuration characteristics of 5 G protocol to maximize the reciprocity of the extracted channel features on the time scale. Secondly, an attention-integrated autoencoder model is proposed to learn the common features in the channel measurements of Alice and Bob. Simulation results show that the proposed method performs better in terms of channel reciprocity enhancement.

•Jul 12, 2025•0 citations

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

Qingjiang Xiao, Jinrong Zhao, Sheng Feng +2 more

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 and Safety•Jul 13, 2023•31 citations

Lightweight Security Solutions for IoT using Physical-Layer Key Generation

Raksha Upadhyay, Ankit Kumar Soni

Modern networking technologies involve the interconnection of smart and intelligent physical objects to provide advanced services. These physical objects may be part of various network technologies like WLAN, wireless sensor network (WSN), Internet of Things (IoT), etc., and share data in wireless mode, which should be secured from threats. These physical devices possess many constraints like power, computational complexity and storage, and are required to have lightweight security algorithms. Traditionally, security is achieved by the higher layers of the communication model, which has high computational complexity and consumes more power. In this chapter, a secure-key-generation scheme from physical layer characteristics is introduced as a possible lightweight security alternative to traditional upper-layer security approaches. The proposed scheme is based on the wiretap-channel model and security is achieved by generating keys at both communicating ends independently, based on inherent common-channel characteristics like randomness. It is mainly based on the principle of spatial decorrelation and channel reciprocity for identical carrier frequency. There is no provision for sharing keys as in public-key cryptography, so physical-layer key generation is not vulnerable to threats like key leakage. The generated key at the transmitter encrypts plain text; the generated cipher is transmitted on the common channel and is decrypted at the receiver end using the key generated by the receiver. Key generation consists of fundamental blocks like channel probing and quantization followed by information reconciliation and privacy amplification. The physical-layer key generation is already a power-efficient security solution; this chapter aims to enhance this capacity further. This is done by introducing low-end signal conditioning in the channel-probing step using moving-window averaging. This solution not only improves system performance but also makes it suitable for limited- power applications. The performance of the key-generation system is characterised in terms of the bit-disagreement rate between the generated key sequences of communicating parties and the key randomness by means of the NIST statistical test suite.

Chapman & Hall/CRC eBooks•Jul 14, 2021•0 citations

Physical Layer Key Generation in 5G and Beyond Wireless Communications: Challenges and Opportunities

Guyue Li, Chen K. Sun, Junqing Zhang +3 more

The fifth generation (5G) and beyond wireless communications will transform many exciting applications and trigger massive data connections with private, confidential, and sensitive information. The security of wireless communications is conventionally established by cryptographic schemes and protocols in which the secret key distribution is one of the essential primitives. However, traditional cryptography-based key distribution protocols might be challenged in the 5G and beyond communications because of special features such as device-to-device and heterogeneous communications, and ultra-low latency requirements. Channel reciprocity-based key generation (CRKG) is an emerging physical layer-based technique to establish secret keys between devices. This article reviews CRKG when the 5G and beyond networks employ three candidate technologies: duplex modes, massive multiple-input multiple-output (MIMO) and mmWave communications. We identify the opportunities and challenges for CRKG and provide corresponding solutions. To further demonstrate the feasibility of CRKG in practical communication systems, we overview existing prototypes with different IoT protocols and examine their performance in real-world environments. This article shows the feasibility and promising performances of CRKG with the potential to be commercialized.

Entropy•May 15, 2019•106 citations
The fifth-generation mobile communication technology (5G) supports wireless data transmission across civil, commercial, industrial, and even military networks, where vast amounts of privacy data are constantly transmitted. However, the open nature of the air interface in 5G systems makes them vulnerable to various attacks. Physical-layer key generation (PKG) has been recognized as a highly promising technology for ensuring data security in 5G systems, while existing PKG schemes achieve low key entropy (i.e., low key randomness) due to poor channel probing and quantization. In this paper, we propose a PKG scheme with high key entropy, tailored to the unique characteristics of 5G systems. First, we design a channel probing method based on the demodulation reference signal in accordance with 5G standards, enhancing the similarity between channel measurements. Next, we introduce a quantization method based on local increment and monotonicity, which effectively leverages channel characteristics to achieve high-speed key generation and improve key entropy. Finally, we use both MATLAB simulation and real-world channel measurements to achieve comprehensive verification of the proposed scheme. The simulation results showed that the proposed scheme increases the key entropy by at least 25% with nearly the same key generation rate compared with existing PKG schemes for 5G systems. The experiment using real-world channel measurements also confirmed that the proposed scheme has higher key entropy.
Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.
Physical layer key generation (PLKG) offers a lightweight and low-complexity key management solution for future emerging wireless communication networks. However, current PLKG schemes face challenges in effective integration with practical communication systems, hindering their practical deployment. To solve this problem, this paper proposes a key generation scheme integrated with the 5 G physical layer protocol, leveraging the Demodulation Reference Signal (DM-RS) to extract channel estimation for PLKG, enabling efficient key generation. Furthermore, a soft-decision quantization method based on Multibit Adaptive Quantization is proposed which makes key reconciliation input compatible with the soft-decision input requirements of the Low-Density Parity-Check (LDPC) decoder in 5G channel coding module. Simulation results demonstrate that the proposed scheme successfully integrates into the 5G standard communication framework while still maintaining favorable key disagreement rate (KDR) performance, the key reconciliation using keys derived by soft-decision quantization method can achieve better key agreement performance than using keys derived by binary quantization.
The fifth generation (5G\mathbf{5 G}5G) communication is progressively being commercialized and civilianized. It is crucial to protect the wireless transmission of sensitive information. Physical layer key generation (PLKG) emerges as a lightweight symmetric key generation technique based on channel reciprocity, which can further ensure the security of 5 G communications. Aiming at the problem of weak channel reciprocity in 5 G communications, this paper proposes a 5G PLKG scheme based on an attention-integrated autoencoder. Firstly, channel probing time slots are planned in accordance with the slot configuration characteristics of 5 G protocol to maximize the reciprocity of the extracted channel features on the time scale. Secondly, an attention-integrated autoencoder model is proposed to learn the common features in the channel measurements of Alice and Bob. Simulation results show that the proposed method performs better in terms of channel reciprocity enhancement.
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.
Modern networking technologies involve the interconnection of smart and intelligent physical objects to provide advanced services. These physical objects may be part of various network technologies like WLAN, wireless sensor network (WSN), Internet of Things (IoT), etc., and share data in wireless mode, which should be secured from threats. These physical devices possess many constraints like power, computational complexity and storage, and are required to have lightweight security algorithms. Traditionally, security is achieved by the higher layers of the communication model, which has high computational complexity and consumes more power. In this chapter, a secure-key-generation scheme from physical layer characteristics is introduced as a possible lightweight security alternative to traditional upper-layer security approaches. The proposed scheme is based on the wiretap-channel model and security is achieved by generating keys at both communicating ends independently, based on inherent common-channel characteristics like randomness. It is mainly based on the principle of spatial decorrelation and channel reciprocity for identical carrier frequency. There is no provision for sharing keys as in public-key cryptography, so physical-layer key generation is not vulnerable to threats like key leakage. The generated key at the transmitter encrypts plain text; the generated cipher is transmitted on the common channel and is decrypted at the receiver end using the key generated by the receiver. Key generation consists of fundamental blocks like channel probing and quantization followed by information reconciliation and privacy amplification. The physical-layer key generation is already a power-efficient security solution; this chapter aims to enhance this capacity further. This is done by introducing low-end signal conditioning in the channel-probing step using moving-window averaging. This solution not only improves system performance but also makes it suitable for limited- power applications. The performance of the key-generation system is characterised in terms of the bit-disagreement rate between the generated key sequences of communicating parties and the key randomness by means of the NIST statistical test suite.
The fifth generation (5G) and beyond wireless communications will transform many exciting applications and trigger massive data connections with private, confidential, and sensitive information. The security of wireless communications is conventionally established by cryptographic schemes and protocols in which the secret key distribution is one of the essential primitives. However, traditional cryptography-based key distribution protocols might be challenged in the 5G and beyond communications because of special features such as device-to-device and heterogeneous communications, and ultra-low latency requirements. Channel reciprocity-based key generation (CRKG) is an emerging physical layer-based technique to establish secret keys between devices. This article reviews CRKG when the 5G and beyond networks employ three candidate technologies: duplex modes, massive multiple-input multiple-output (MIMO) and mmWave communications. We identify the opportunities and challenges for CRKG and provide corresponding solutions. To further demonstrate the feasibility of CRKG in practical communication systems, we overview existing prototypes with different IoT protocols and examine their performance in real-world environments. This article shows the feasibility and promising performances of CRKG with the potential to be commercialized.