This paper presents a new class of precoder-based Physical Layer Security (PLS) algorithms for 6G mobile networks, a significant advancement that combines security and ultra-reliable low latency communications (S-URLLC). The paper also explores the potential of S-URLLC algorithms for realtime shared secret key information exchange in Layer-1 transmission and proposes AI/ML-based detection algorithms for natively securing future 6G-IoT networks against remote eavesdropping. The paper marries a temporal-spatial M-dimensional code with operator matrices drawn from the class of random unitary (precoder) operators to jointly guarantee ultra-reliability and security. The code delivers ultra-reliability, while the precoder operator safeguards the signal waveform from eavesdroppers. The shared secret key-based model operating within a Hyper-Dimensional Temporal-Spatial Precoding with ML-based decoding (HD-TSP-ML) scheme scales across multi-antenna array sizes and codebook modulation orders and delivers impressive 1215 dB improvements in link reliability. The security analysis of Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) of intended receiver versus eavesdropper reveals a low probability of interception by malicious eavesdroppers, even when the passive eavesdropper observes in a high SNR, correlated channel with the intended recipient. The paper presents a system architecture of the shared secret key HD-TSP-ML model, discusses simulation result evaluation of the BER of secret information exchanged for the algorithm in Rayleigh fading plus noise and analyzes numerical model of the transmit data-rate versus MIMO array size as well as latency for the system along with a complexity analysis.
This paper presents a new class of precoder-based Physical Layer Security (PLS) algorithms for 6G mobile networks, a significant advancement that combines security and ultra-reliable low latency communications (S-URLLC). The paper also explores the potential of S-URLLC algorithms for realtime shared secret key information exchange in Layer-1 transmission and proposes AI/ML-based detection algorithms for natively securing future 6G-IoT networks against remote eavesdropping. The paper marries a temporal-spatial M-dimensional code with operator matrices drawn from the class of random unitary (precoder) operators to jointly guarantee ultra-reliability and security. The code delivers ultra-reliability, while the precoder operator safeguards the signal waveform from eavesdroppers. The shared secret key-based model operating within a Hyper-Dimensional Temporal-Spatial Precoding with ML-based decoding (HD-TSP-ML) scheme scales across multi-antenna array sizes and codebook modulation orders and delivers impressive 1215 dB improvements in link reliability. The security analysis of Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) of intended receiver versus eavesdropper reveals a low probability of interception by malicious eavesdroppers, even when the passive eavesdropper observes in a high SNR, correlated channel with the intended recipient. The paper presents a system architecture of the shared secret key HD-TSP-ML model, discusses simulation result evaluation of the BER of secret information exchanged for the algorithm in Rayleigh fading plus noise and analyzes numerical model of the transmit data-rate versus MIMO array size as well as latency for the system along with a complexity analysis.
Ultra-reliable low latency communication (URLLC) is an innovative service offered by fifth-generation (5G) wireless systems. URLLC enables various mission-critical applications by facilitating reliable and low-latency signal transmission. Apart from reliability and latency, ensuring the security of URLLC data transmission has been a prominent issue in recent years. URLLC uses finite blocklength signals to achieve the stringent reliability and latency requirement which eliminates the possibility of using conventional complex secret key-based cryptographic techniques. In this regard, lightweight security mechanisms like physical layer Security (PLS) have emerged as a powerful alternative to the complex cryptographic security techniques for URLLC by exploiting the randomness of the wireless channel. Therefore, this survey presents a comprehensive and in-depth review of the state-of-the-art PLS enhancements utilized to unleash secure URLLC in 5G and upcoming sixth-generation (6G) wireless networks. Moreover, the survey discusses the impact of system design parameters on the PLS of URLLC. It also incorporates a detailed overview of the recent advancements in ensuring PLS for mission-critical applications, URLLC enabling technologies, and Machine Learning (ML) based intelligent PLS schemes for URLLC. Then, for the first time, the survey introduces the extended service class of URLLC in 6G, i.e., Hyper Reliable Low Latency Communication (HRLLC), and provides an outlook on the future security aspects while identifying various promising new technologies that can provide secure HRLLC in 6G. Finally, the survey identifies several key challenges and highlights interesting future research directions while developing optimal PLS schemes for URLLC in 5G and HRLLC in future 6G wireless networks.
Ultra-reliable low latency communication (URLLC) is an innovative service offered by fifth-generation (5G) wireless systems. URLLC enables various mission-critical applications by facilitating reliable and low-latency signal transmission to support extreme Quality of Service (QoS) requirements. Apart from reliability and latency, ensuring secure data transmission for URLLC has been a prominent issue for researchers in recent years. Using finite blocklength signals to achieve the stringent reliability and latency criteria in URLLC eliminates the possibility of using conventional complex cryptographic security enhancement techniques based on encoding and decoding of secret keys. Thus, the development of lightweight security mechanisms is of paramount importance for URLLC. Recently, Physical-Layer Security (PLS) techniques have emerged as a powerful alternative to the complex cryptography-based security approaches for facilitating secure URLLC by exploiting the randomness of the wireless channel. Therefore, in this survey, we present a comprehensive and in-depth review of the state-of-the-art PLS enhancements utilized to unleash secure URLLC while analyzing the impact of various system design parameters on its performance. Moreover, the survey incorporates a detailed overview of the recent advancements in ensuring secure URLLC using PLS in various mission-critical applications, and 5G URLLC enabling technologies like non-orthogonal multiple access (NOMA), multi-antenna systems, cooperative communication using unmanned aerial vehicles (UAV), and intelligent reflective surfaces (IRS). Apart from this, we briefly discuss the role of advanced Machine Learning (ML) techniques in designing robust and intelligent PLS schemes for URLLC service.
In this paper, we propose enhancing physical layer security (PLS) of ultra-reliable low latency communication (URLLC) in a full-duplex cooperative non-orthogonal multiple access (FD-CNOMA) based Internet of Things (IoT) network. We analyze the PLS performance of a two-user FD-CNOMA system, where a source node transmits the short packet URLLC information to a near user and a far cell-edge user in the presence of an external eavesdropper. To ensure the security and reliability of URLLC signal transmission, the near user is utilized as a cooperative relay for transmitting the information intended for the far user, and also transmits an artificial noise (AN) signal to mitigate the impact of eavesdropping. An approximate closed-form expression of the average secure block error rate (SBLER) and the average secrecy throughput (AST) of the legitimate users under eavesdropping is derived. The analytical framework presented in this work considers the URLLC signal transmission with and without AN signal while evaluating the impact of residual self-interference (RSI) at the relay node on the PLS performance of the FD-CNOMA system. Thus, to improve the PLS performance and maximize the system AST, we optimize the URLLC blocklength and power allocation coefficient (PAC) at the source. The numerical and simulation results validate the proposed analytical framework and demonstrate a significant improvement of average SBLER and overall system AST (SAST) using AN-assisted URLLC signal transmission in the FD-CNOMA system.
If Beyond-5G(B5G)/6G is to support critical infrastructure worldwide, there must be an effort to jointly integrate low latency and privacy into wireless protocols. This research analyzes new schemes for securing applications at low latency by extending Physical Layer Security (PLS) algorithms to B5G/6G systems. We design protocols that advance a specific form of Physical Layer Security, known as Key-based Physical Layer Security, from the theoretical realm into the practical. One form of a Key-based algorithm obscures information from eavesdroppers by mapping it to cleverly rotated reference signals. For such a scheme, prior work has found that the two-way exchange of completely private information involves six OFDM symbol times, not including synchronization. By developing a protocol that makes the most optimum use of time-frequency resources, we show that it is possible to achieve two-way private exchange and synchronization in only four symbol times - the least latency possible. A significant simulation result indicates that our improved protocol achieves sub-1 ms two-way latency, including re-transmissions. We also illustrate a protocol that shows how Key-based Physical Layer Security can privatize critical PHY layer functions such as cell search. Lastly, additional results show the performance of the PLS algorithm in terms of Key Bit Error Rates and secret key transmission rates.
Due to the openness nature of wireless medium, security issues have increasingly become a bottleneck that restricts the development of ultra-reliable and low-latency communications (uRLLCs). Physical layer security (PLS) technique has been proposed to fulfill the security and confidentiality of information transmission by exploiting the characteristics of the wireless channel, which caters to the features of uRLLC. Furthermore, PLS also shows great practicality in artificial intelligence field, especially in wireless intelligent networks. However, the previous works on the study of PLS ignored the significance of mobility and limited packet length constraint required by uRLLC for satisfying low latency, in this paper, we investigate the impact of mobility on the secrecy performance of uRLLC by using the Random WayPoint (RWP) model and the Random Direction (RD) model. Specifically, with the tools of stochastic geometry, to observe the impact of key system parameters on the secrecy performance, we establish the closed-form expression of connection outage probability, secrecy outage probability, and decoding error probability-based secrecy transmission capacity (DEP-STC). Furthermore, we derive the condition that achieves a positive DEP-STC under two moving models, which can offer the network designer some greatly significant insights into achieving perfect secrecy. Simulations validate our derived theoretical results, and indicate that RWP moving receiver can obtain a higher security level than RD moving one, while RWP eavesdropper can lead to a lower security.
In the fast-evolving communication systems, we are currently in the 5 G phase and continuously progressing toward the 6th generation spectrum. Ultra-Reliable Low Latency Communication (URLLC) and Hyper-Reliable Low Latency Communication (HRLLC) are the cutting-edge services offered by 5G and 6G wireless systems, enabling more missioncritical applications by employing highly reliable and low latency signal transmission. Apart from applications emphasize reliability and low latency, this study focuses on a lightweight security mechanism known as Physical Layer Security (PLS), which is an essential requirement to enable secure data transmission in mission-critical applications. URLLC/HRLLC uses finite block length (FBL) signals to achieve stringent reliability and latency requirements, thereby eliminating the need for traditional key-based cryptographic techniques. Then the Channel State Information (CSI) value and signal block length, are correspondingly introduced. Therefore, this survey presents a comprehensive and detailed study on the PLS of URLLC/HRLLC in 5G and beyond communications. This paper mainly concentrates on the current enhancements in PLS for mission-critical applications and provides an in-depth review of finite block length-oriented and CSI-driven strategies employed in URLLC/HRLLC. This review emphasizes state-of-the-art robust and adaptive CSI-based security frameworks that address channel estimation errors. The Novel Idea of this study is to introduce a unified design oriented PLS frame work that integrates FBL communication theory and Practical CSI limitations in wireless networks Finally, the survey discusses several key challenges and identifies open research directions in joint FBL-CSI optimization, secure training signal design, and energy-efficient secrecy protocols for future 6 G wireless networks.