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Sensors
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Security and Privacy in Wireless Communication and Internet of Things
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Security and Privacy in Wireless Communication and Internet of Things

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

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 4697

Special Issue Editors

Dr. Qinghua Wang

E-Mail Website
Guest Editor
Department of Computer Science, Faculty of Natural Sciences, Kristianstad University, SE-29188 Kristianstad, Sweden
Interests: Internet of Things; big data; future internet; network security
Prof. Dr. Mikael Gidlund

E-Mail Website
Guest Editor
Department of Information Systems and Technology, Mid Sweden University, 852 30 Sundsvall, Sweden
Interests: wireless communication; wireless sensor networks; wireless coexistence; signal processing; network security
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zheng Yan

E-Mail Website
Guest Editor
State Key Laboratory on Integrated Services Networks, School of Cyber Engineering, Xidian University, Xi’an 710071, China
Interests: information security and privacy; trust modeling and management; trusted computing; trust, security and privacy in social networking and IoT
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Rahim Rahmani

E-Mail Website
Guest Editor
Department of Computer and Systems Sciences, Stockholm University, 16407 Stockholm, Sweden
Interests: distributed data processing in distributed IoT; cognitive edge continuum; tactile internet, and large-scale decentralized systems (blockchain)

Special Issue Information

Dear Colleagues,

Recent developments in wireless communication and Internet of Things (IoT) have enabled many new applications, and are dramatically changing our lives. The IoT interconnects people, networks, fog/edge, cloud, sensors, actuators, and physical environments to make networking and wireless communication more relevant and valuable than ever before. However, there are problems such as hardware resource constraints, lack of dominating standards, lack of interoperability among different service providers and different communication platforms. These problems make it challenging to design and provide security solutions for wireless communication and IoT. Meanwhile, many security- and privacy-sensitive applications, such as process industry applications, intelligent transportation systems, smart city and smart home applications, as well as remote healthcare applications, are heavily dependent on wireless communication and IoT. It is therefore imperative to study the security and privacy solutions for wireless communication and IoT with regards to the newest development trends in both technology and applications. With this Special Issue, we solicit original contributions on security and privacy in wireless communication and IoT, such as physical-layer security, network security, human factors, blockchain applications, privacy preservation with federated learning, intrusion detection, lightweight cryptography, quantum cryptography for IoT, and experiences from providing security for real-world mobile and IoT applications.

Dr. Qinghua Wang
Prof. Dr. Mikael Gidlund
Prof. Dr. Zheng Yan
Prof. Dr. Rahim Rahmani
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. 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

  • blockchain
  • human factors in cybersecurity
  • IoT security
  • lightweight cryptography
  • mobile security
  • network security
  • physical-layer security
  • privacy preserving

Published Papers (3 papers)

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Research

24 pages, 1759 KiB  
Article
Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm
by Mahrukh Ramzan, Muhammad Shoaib, Ayesha Altaf, Shazia Arshad, Faiza Iqbal, Ángel Kuc Castilla and Imran Ashraf
Sensors 2023, 23(20), 8642; https://doi.org/10.3390/s23208642 - 23 Oct 2023
Cited by 2 | Viewed by 2296
Abstract
Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (DoS) attacks, distributed DoS (DDoS) attacks, [...] Read more.
Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (DoS) attacks, distributed DoS (DDoS) attacks, code injection attacks, and spoofing are the most common types of attacks in the modern era. Due to the expansion of IT, the volume and severity of network attacks have been increasing lately. DoS and DDoS are the most frequently reported network traffic attacks. Traditional solutions such as intrusion detection systems and firewalls cannot detect complex DDoS and DoS attacks. With the integration of artificial intelligence-based machine learning and deep learning methods, several novel approaches have been presented for DoS and DDoS detection. In particular, deep learning models have played a crucial role in detecting DDoS attacks due to their exceptional performance. This study adopts deep learning models including recurrent neural network (RNN), long short-term memory (LSTM), and gradient recurrent unit (GRU) to detect DDoS attacks on the most recent dataset, CICDDoS2019, and a comparative analysis is conducted with the CICIDS2017 dataset. The comparative analysis contributes to the development of a competent and accurate method for detecting DDoS attacks with reduced execution time and complexity. The experimental results demonstrate that models perform equally well on the CICDDoS2019 dataset with an accuracy score of 0.99, but there is a difference in execution time, with GRU showing less execution time than those of RNN and LSTM. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communication and Internet of Things)
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14 pages, 401 KiB  
Communication
Secrecy Performance Analysis of Backscatter Communications with Side Information
by Masoud Kaveh, Farshad Rostami Ghadi, Riku Jäntti and Zheng Yan
Sensors 2023, 23(20), 8358; https://doi.org/10.3390/s23208358 - 10 Oct 2023
Cited by 2 | Viewed by 765
Abstract
Backscatter communication (BC) systems are a promising technology for internet of things (IoT) applications that allow devices to transmit information by modulating ambient radio signals without the need for a dedicated power source. However, the security of BC systems is a critical concern [...] Read more.
Backscatter communication (BC) systems are a promising technology for internet of things (IoT) applications that allow devices to transmit information by modulating ambient radio signals without the need for a dedicated power source. However, the security of BC systems is a critical concern due to the vulnerability of the wireless channel. This paper investigates the impact of side information (SI) on the secrecy performance of BC systems. SI mainly refers to the additional knowledge that is available to the communicating parties beyond transmitted data, which can be used to enhance reliability, efficiency, security, and quality of service in various communication systems. In particular, in this paper, by considering a non-causally known SI at the transmitter, we derive compact analytical expressions of average secrecy capacity (ASC) and secrecy outage probability (SOP) for the proposed system model to analyze how SI affects the secrecy performance of BC systems. Moreover, a Monte Carlo simulation validates the accuracy of our analytical results and reveals that considering such knowledge at the transmitter has constructive effects on the system performance and ensures reliable communication with higher rates than the conventional BC systems without SI, namely, lower SOP and higher ASC are achievable. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communication and Internet of Things)
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19 pages, 1207 KiB  
Article
Inter-Frame-Relationship Protected Signal: A New Design for Radio Frequency Fingerprint Authentication
by Xufei Li, Shuiguang Zeng and Yangyang Liu
Sensors 2023, 23(15), 6948; https://doi.org/10.3390/s23156948 - 04 Aug 2023
Viewed by 694
Abstract
Utilizing a multi-frame signal (MFS) rather than a single-frame signal (SFS) for radio frequency fingerprint authentication (RFFA) shows the advantage of higher accuracy. However, previous studies have often overlooked the associated security threats in MFS-based RFFA. In this paper, we focus on the [...] Read more.
Utilizing a multi-frame signal (MFS) rather than a single-frame signal (SFS) for radio frequency fingerprint authentication (RFFA) shows the advantage of higher accuracy. However, previous studies have often overlooked the associated security threats in MFS-based RFFA. In this paper, we focus on the carrier-sense multiple access with collision avoidance channel and identify a potential security threat, in that an attacker may inject a forged frame into valid traffic, making it more likely to be accepted alongside legitimate frames. To counter such a security threat, we propose an innovative design called the inter-frame-relationship protected signal (IfrPS), which enables the receiver to determine whether two consecutively received frames originate from the same transmitter to safeguard the MFS-based RFFA. To demonstrate the applicability of our proposition, we analyze and numerically evaluate two important properties: its impact on message demodulation and the accuracy gain in IfrPS-aided, MFS-based RFFA compared with the SFS-based RFFA. Our results show that the proposed scheme has a minimal impact of only −0.5 dB on message demodulation, while achieving up to 5 dB gain for RFFA accuracy. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Communication and Internet of Things)
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