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Security and Privacy in Wireless Communications and Networking
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Security and Privacy in Wireless Communications and Networking

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 7500

Special Issue Editor

Prof. Dr. Jie Tang

E-Mail Website
Guest Editor
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: wireless communications and physical layer security

Special Issue Information

Dear Colleagues,

Wireless Communications and Networking promise to meet the continuously increasing demands of wireless mobile applications, such as self-driving vehicles, smart cities, military and government applications, and so on. With the substantial increase in coverage and network heterogeneity, there are severe concerns that security and privacy in the future wireless communications and networking can be worse than the previous generations, for example, when the massive amount of resource-constrained IoT (Internet of Things) devices and sensors will be connected by the future wireless networks. Wireless sensors and actuators connected by the IoT are central to the design of advanced cyber-physical systems (CPSs). In such complex, heterogeneous systems, communication links must meet stringent requirements on throughput, latency, and range, while adhering to tight energy budget and providing high levels of security. On the other hand, the involvement of connected devices in every aspect of humans (e.g., implants/cyborgs) poses serious concerns of potential leaks of personal information (e.g., health records). Potential loss from security attacks could be irrecoverable, not only about finance or personal reputation as it is currently but also about life.

This Special Issue is addressed to all types of advanced security and privacy research papers for wireless communications and networking and cyber-physical systems.

Prof. Dr. Jie Tang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wireless communications security；network security；security and privacy
  • Internet-of Things
  • sensors and actuators
  • 5G and 6G security
  • cyber-physical systems
  • physical layer security
  • artificial intelligence
  • edge computing
  • automatic control network
  • 3C security design

Published Papers (4 papers)

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Research

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19 pages, 713 KiB  
Article
Machine-Learning-Assisted Cyclostationary Spectral Analysis for Joint Signal Classification and Jammer Detection at the Physical Layer of Cognitive Radio
by Tassadaq Nawaz and Ali Alzahrani
Sensors 2023, 23(16), 7144; https://doi.org/10.3390/s23167144 - 12 Aug 2023
Cited by 3 | Viewed by 1519
Abstract
Cognitive radio technology was introduced as a possible solution for spectrum scarcity by exploiting dynamic spectrum access. In the last two decades, most researchers focused on enabling cognitive radios for managing the spectrum. However, due to their intelligent nature, cognitive radios can scan [...] Read more.
Cognitive radio technology was introduced as a possible solution for spectrum scarcity by exploiting dynamic spectrum access. In the last two decades, most researchers focused on enabling cognitive radios for managing the spectrum. However, due to their intelligent nature, cognitive radios can scan the radio frequency environment and change their transmission parameters accordingly on-the-fly. Such capabilities make it suitable for the design of both advanced jamming and anti-jamming systems. In this context, our work presents a novel, robust algorithm for spectrum characterisation in wideband radios. The proposed algorithm considers that a wideband spectrum is sensed by a cognitive radio terminal. The wideband is constituted of different narrowband signals that could either be licit signals or signals jammed by stealthy jammers. Cyclostationary feature detection is adopted to measure the spectral correlation density function of each narrowband signal. Then, cyclic and angular frequency profiles are obtained from the spectral correlation density function, concatenated, and used as the feature sets for the artificial neural network, which characterise each narrowband signal as a licit signal with a particular modulation scheme or a signal jammed by a specific stealthy jammer. The algorithm is tested under both multi-tone and modulated stealthy jamming attacks. Results show that the classification accuracy of our novel algorithm is superior when compared with recently proposed signal classifications and jamming detection algorithms. The applications of the algorithm can be found in both commercial and military communication systems. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communications and Networking)
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12 pages, 340 KiB  
Article
A Bilevel Optimization Model Based on Edge Computing for Microgrid
by Yi Chen, Kadhim Hayawi, Meikai Fan, Shih Yu Chang, Jie Tang, Ling Yang, Rui Zhao, Zhongqi Mao and Hong Wen
Sensors 2022, 22(20), 7710; https://doi.org/10.3390/s22207710 - 11 Oct 2022
Cited by 3 | Viewed by 1350
Abstract
With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging [...] Read more.
With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control module and a lower-level optimal control module. The purpose of the two-layer optimization modules is to optimize the cost of the power distribution of microgrids. The function of the upper-level optimal control module is to set decision variables for the lower-level module, while the function of the lower-level module is to find the optimal solution by mathematical methods on the basis of the upper-level and then feed back the optimal solution to the upper-layer. The upper-level and lower-level modules affect system decisions together. Finally, the feasibility of the bilevel optimization model is demonstrated by experiments. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communications and Networking)
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15 pages, 347 KiB  
Article
Vector Auto-Regression-Based False Data Injection Attack Detection Method in Edge Computing Environment
by Yi Chen, Kadhim Hayawi, Qian Zhao, Junjie Mou, Ling Yang, Jie Tang, Qing Li and Hong Wen
Sensors 2022, 22(18), 6789; https://doi.org/10.3390/s22186789 - 8 Sep 2022
Cited by 6 | Viewed by 1522
Abstract
With the wide application of advanced communication and information technology, false data injection attack (FDIA) has become one of the significant potential threats to the security of smart grid. Malicious attack detection is the primary task of defense. Therefore, this paper proposes a [...] Read more.
With the wide application of advanced communication and information technology, false data injection attack (FDIA) has become one of the significant potential threats to the security of smart grid. Malicious attack detection is the primary task of defense. Therefore, this paper proposes a method of FDIA detection based on vector auto-regression (VAR), aiming to improve safe operation and reliable power supply in smart grid applications. The proposed method is characterized by incorporating with VAR model and measurement residual analysis based on infinite norm and 2-norm to achieve the FDIA detection under the edge computing architecture, where the VAR model is used to make a short-term prediction of FDIA, and the infinite norm and 2-norm are utilized to generate the classification detector. To assess the performance of the proposed method, we conducted experiments by the IEEE 14-bus system power grid model. The experimental results demonstrate that the method based on VAR model has a better detection of FDIA compared to the method based on auto-regressive (AR) model. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communications and Networking)
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Review

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32 pages, 8148 KiB  
Review
The Use of Computational Geometry Techniques to Resolve the Issues of Coverage and Connectivity in Wireless Sensor Networks
by Sharmila Devi, Anju Sangwan, Anupma Sangwan, Mazin Abed Mohammed, Krishna Kumar, Jan Nedoma, Radek Martinek and Petr Zmij
Sensors 2022, 22(18), 7009; https://doi.org/10.3390/s22187009 - 16 Sep 2022
Cited by 2 | Viewed by 2227
Abstract
Wireless Sensor Networks (WSNs) enhance the ability to sense and control the physical environment in various applications. The functionality of WSNs depends on various aspects like the localization of nodes, the strategies of node deployment, and a lifetime of nodes and routing techniques, [...] Read more.
Wireless Sensor Networks (WSNs) enhance the ability to sense and control the physical environment in various applications. The functionality of WSNs depends on various aspects like the localization of nodes, the strategies of node deployment, and a lifetime of nodes and routing techniques, etc. Coverage is an essential part of WSNs wherein the targeted area is covered by at least one node. Computational Geometry (CG) -based techniques significantly improve the coverage and connectivity of WSNs. This paper is a step towards employing some of the popular techniques in WSNs in a productive manner. Furthermore, this paper attempts to survey the existing research conducted using Computational Geometry-based methods in WSNs. In order to address coverage and connectivity issues in WSNs, the use of the Voronoi Diagram, Delaunay Triangulation, Voronoi Tessellation, and the Convex Hull have played a prominent role. Finally, the paper concludes by discussing various research challenges and proposed solutions using Computational Geometry-based techniques. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communications and Networking)
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