Hina Ayaz, Ghulam Abbas, Muhammad Waqas, Ziaul Haq Abbas, Muhammad Bilal, Ali Nauman, Muhammad Ali Jamshed
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引用次数: 1
Abstract
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, low-delay, 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.
期刊介绍:
IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems. The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more.
Topics covered by scope include, but are not limited to:
advances in single and multi-dimensional filter design and implementation
linear and nonlinear, fixed and adaptive digital filters and multirate filter banks
statistical signal processing techniques and analysis
classical, parametric and higher order spectral analysis
signal transformation and compression techniques, including time-frequency analysis
system modelling and adaptive identification techniques
machine learning based approaches to signal processing
Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques
theory and application of blind and semi-blind signal separation techniques
signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals
direction-finding and beamforming techniques for audio and electromagnetic signals
analysis techniques for biomedical signals
baseband signal processing techniques for transmission and reception of communication signals
signal processing techniques for data hiding and audio watermarking
sparse signal processing and compressive sensing
Special Issue Call for Papers:
Intelligent Deep Fuzzy Model for Signal Processing - https://digital-library.theiet.org/files/IET_SPR_CFP_IDFMSP.pdf