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Electronics
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Security and Privacy for Modern Wireless Communication Systems, 2nd Edition
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Security and Privacy for Modern Wireless Communication Systems, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 1591

Special Issue Editors

Dr. Tao Huang

E-Mail Website
Guest Editor
College of Science and Engineering, James Cook University, Smithfield, QLD 4878, Australia
Interests: deep learning; intelligent sensing; computer vision; pattern recognition; wireless communications; IoT security
Special Issues, Collections and Topics in MDPI journals
Dr. Shihao Yan

E-Mail Website
Guest Editor
School of Science, Edith Cowan University, Perth, Australia 270 Joondalup Drive, Joondalup WA 6027,Australia
Interests: UAV-aided communications; covert communications; covert sensing; location spoofing detection; physical layer security; and IRS-aided wireless communications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Guanglin Zhang

E-Mail Website
Guest Editor
Department of Communication Engineering, College of Information Science and Technology, Donghua University, Shanghai 201620, China
Interests: mobile edge computing offloading; reinforcement learning for microgrids; online learning for VANET caching optimization for wireless networks; SDN and applications in UAV and the IoT for industry applications
Special Issues, Collections and Topics in MDPI journals
Dr. Tsz Hon Yuen

E-Mail Website
Guest Editor
Department of Computer Science, University of Hong Kong, Pokfulam 999077, Hong Kong
Interests: cryptography; privacy-preserving protocols; blockchain
Special Issues, Collections and Topics in MDPI journals
Dr. YoHan Park

E-Mail Website
Guest Editor
Next-generation Information Security Laboratory(NISL), College of Engineering, Keimyung University, Daegu, 24601, Republic of Korea
Interests: network security; security of IoT; blockchain; post-quantum cryptography; security of VANETs; formal analysis
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Changhoon Lee

E-Mail Website
Guest Editor
Department of Computer Science & Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea
Interests: cyber threat intelligence (CTI); information security; digital forensics; IoT and Cloud security; cryptography
Special Issues, Collections and Topics in MDPI journals
Dr. Jusak Jusak

E-Mail Website
Guest Editor
School of Science and Technology, James Cook University, Singapore 387380, Singapore
Interests: IoT communication networks and protocol; IoT for healthcare; low-power wide-area IoT networks; IoT security; integration between IoT and blockchain technology

Special Issue Information

Dear Colleagues,

Security and privacy have consistently been crucial concerns within wireless communication systems. To address these concerns effectively, innovative approaches to cryptography, physical layer transmission strategies, network protocols, and related regulations are in high demand. Over the past decade, wireless communication networks have witnessed significant advancements and transformations across various dimensions.

Primarily, the research focus within wireless communication systems has shifted from 5G to 6G, leading to heightened device connectivity and information flow within wireless networks. This transition has been accompanied by the emergence of novel applications, such as remote real-time medical services and patient care, which necessitate the exclusive reception and processing of confidential data by designated service providers.

Secondly, the development of the Internet of Things (IoT) has emerged as a key catalyst for automation in diverse domains, including smart homes, precision agriculture, and intelligent manufacturing. However, the design parameters for IoT systems, such as packet length, transmission patterns, and time delays, exhibit significant variations across different applications. Consequently, these variations present distinct challenges in security and privacy design. Notably, integrating lightweight cryptography is imperative to cater to the power constraints inherent in IoT systems.

Thirdly, the development and introduction of new technologies, such as intelligent reflection surfaces, edge/fog/cloud computing, blockchain, and artificial intelligence (AI), into the wireless communication system design bring new opportunities and challenges in guaranteeing information security and user privacy.

This Special Issue focuses on the latest research in protocols, software/hardware development and implementation, and system architecture design that addresses the emerging security and privacy issues in modern wireless communication networks. The scope of this Issue encompasses various relevant topics, including but not limited to the following:

  • Deep-learning-based security and privacy design;
  • Covert communications;
  • Security in UAV-assisted networks;
  • Information‒theoretical foundations for advanced security and privacy techniques;
  • Lightweight cryptography for power-constrained networks;
  • Physical layer key generation;
  • Prototype and testbed for security and privacy solutions;
  • Encryption and decryption algorithm for low-latency-constrained networks;
  • Security protocols for modern wireless communication networks;
  • Network intrusion detection;
  • Physical layer design with security consideration;
  • Anonymity in data transmission;
  • Vulnerabilities in security and privacy in modern wireless communication networks;
  • Challenges of security and privacy in node‒edge‒cloud computation;
  • Security and privacy design for low-power wide-area IoT networks;
  • Security and privacy design for vehicle networks;
  • Security and privacy design for underwater communications network;
  • Blockchain-based solutions for modern wireless communication networks.

Dr. Tao Huang
Dr. Shihao Yan
Prof. Dr. Guanglin Zhang
Dr. Tsz Hon Yuen
Dr. YoHan Park
Prof. Dr. Changhoon Lee
Dr. Jusak Jusak
Guest Editors

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. Electronics 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 2400 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

  • physical layer security
  • covert communications
  • information‒theoretical foundations
  • lightweight cryptography
  • privacy
  • key generation
  • security protocols
  • intrusion detection
  • machine learning
  • blockchain
  • prototype and testbed

Related Special Issue

Published Papers (2 papers)

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Research

17 pages, 914 KiB  
Article
LoRa Radio Frequency Fingerprinting with Residual of Variational Mode Decomposition and Hybrid Machine-Learning/Deep-Learning Optimization
by Gianmarco Baldini and Fausto Bonavitacola
Electronics 2024, 13(10), 1925; https://doi.org/10.3390/electronics13101925 (registering DOI) - 14 May 2024
Viewed by 259
Abstract
Radio Frequency Fingerprinting (RFF) refers to the technique for identifying and classifying wireless devices on the basis of their physical characteristics, which appear in the digital signal transmitted in space. Small differences in the radio frequency front-end of the wireless devices are generated [...] Read more.
Radio Frequency Fingerprinting (RFF) refers to the technique for identifying and classifying wireless devices on the basis of their physical characteristics, which appear in the digital signal transmitted in space. Small differences in the radio frequency front-end of the wireless devices are generated across the same wireless device model during the implementation and manufacturing process. These differences create small variations in the transmitted signal, even if the wireless device is still compliant with the wireless standard. By using data analysis and machine-learning algorithms, it is possible to classify different electronic devices on the basis of these variations. This technique has been well proven in the literature, but research is continuing to improve the classification performance, robustness to noise, and computing efficiency. Recently, Deep Learning (DL) has been applied to RFF with considerable success. In particular, the combination of time-frequency representations and Convolutional Neural Networks (CNN) has been particularly effective, but this comes at a great computational cost because of the size of the time-frequency representation and the computing time of CNN. This problem is particularly challenging for wireless standards, where the data to be analyzed is extensive (e.g., long preambles) as in the case of the LoRa (Long Range) wireless standard. This paper proposes a novel approach where two pre-processing steps are adopted to (1) improve the classification performance and (2) to decrease the computing time. The steps are based on the application of Variational Mode Decomposition (VMD) where (in opposition to the known literature) the residual of the VMD application is used instead of the extracted modes. The concept is to remove the modes, which are common among the LoRa devices, and keep with the residuals the unique intrinsic features, which are related to the fingerprints. Then, the spectrogram is applied to the residual component. Even after this step, the computing complexity of applying CNN to the spectrogram is high. This paper proposes a novel step where only segments of the spectrogram are used as input to CNN. The segments are selected using a machine-learning approach applied to the features extracted from the spectrogram using the Local Binary Pattern (LBP). The approach is applied to a recent LoRa radio frequency fingerprinting public data set, where it is shown to significantly outperform the baseline approach based on the full use of the spectrogram of the original signal in terms of both classification performance and computing complexity. Full article
(This article belongs to the Special Issue Security and Privacy for Modern Wireless Communication Systems, 2nd Edition)
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14 pages, 3650 KiB  
Article
Forensic Analysis of File Exfiltrations Using AnyDesk, TeamViewer and Chrome Remote Desktop
by Xabiel G. Pañeda, David Melendi, Víctor Corcoba, Alejandro G. Pañeda, Roberto García and Dan García
Electronics 2024, 13(8), 1429; https://doi.org/10.3390/electronics13081429 - 10 Apr 2024
Viewed by 695
Abstract
The use of remote desktop applications has increased greatly in recent years, mainly because of the generalization of telecommuting due to the COVID-19 pandemic. This process has been carried out in a very controlled manner in some companies, but in other organizations it [...] Read more.
The use of remote desktop applications has increased greatly in recent years, mainly because of the generalization of telecommuting due to the COVID-19 pandemic. This process has been carried out in a very controlled manner in some companies, but in other organizations it has been introduced in a more anarchic way. The direct use of on-premises company computers and resources from the internet without the necessary protection mechanisms, including VPNs, has increased the risk of data exfiltration. Apart from other types of data exfiltration, there are cases in which employees transfer files using encrypted communications, consciously or unconsciously, producing a leak of information undetected by data loss prevention systems. In this paper we analyse the question of whether a forensic investigation may answer questions about data exfiltrations; questions such as those regarding the when, what and who (or to whom) and the use of application logs and other available tools. The answers to these questions may form the basis of solid digital evidence for legal purposes, though they may only deliver a partial response to said questions. Other complementary sources are necessary to build a complete answer and accurate digital evidence. Nevertheless, we have identified and analysed several use cases that may help to raise an early alarm that can offer warning about certain behaviours in encrypted traffic that may be detected via network monitoring. Full article
(This article belongs to the Special Issue Security and Privacy for Modern Wireless Communication Systems, 2nd Edition)
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