It is anticipated that sixth-generation (6G) systems would present new security challenges while offering improved features and new directions for security in vehicular communication, which may result in the emergence of a new breed of adaptive and context-aware security protocol. Physical layer security solutions can compete for low-complexity, lowdelay, low-footprint, adaptable, extensible, and context-aware security schemes by leveraging the physical layer and introducing security controls. A novel physical layer security scheme that employs the concept of radio frequency fingerprinting (RF-FP) for location estimation is proposed, wherein the RF-FP values are collected at different points with in the cell. Then, based on the estimated location, the nearest possible road-side unit for sending the information signal is located. After this, the effects on secrecy capacity (SC) and secrecy outage probability (SOP) in the presence of multiple eavesdropper per unit time are analysed. It has been shown via simulations that the proposed RF-FP scheme increases SC by up to 25% for the same signal-to-noise ratio (SNR) values as those of the benchmarks, while the SOP tends to decrease by up to 30% as compared to the benchmark scheme for the same SNR value. Thus, the proposed RF-FP-based location estimation provides much better results as compared to the existing physical layer security schemes.
K E Y W O R D S radio links, security of data
| INTRODUCTION 1.| MotivationThe rapid advancements in wireless communication and the rapid expansion in urbanisation have paved the way for new frontiers in the domain of cellular communication. Sixth Generation (6G) technology is considered to be a new candidate in this line of advancement. 6G has promised to overcome the shortcomings of Fifth Generation (5G) and Beyond 5G (B5G) by exploiting the terahertz (THz) range. One of the features provided by 6G is to reduce latency, that is, reduce the delay in time by 1/100 of a millisecond. 6G is estimated to provide the highest data rates, that is, 1 Tbps, along with much better support for machine to machine communication, energy efficiency, network reliability, and the use of artificial intelligence (AI) and machine learning (ML) for optimal connectivity [1, 2].