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Security and Privacy in Wireless Sensor Networks (WSNs)
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Security and Privacy in Wireless Sensor Networks (WSNs)

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

Deadline for manuscript submissions: 31 March 2025 | Viewed by 3019

Special Issue Editors

Dr. Kamanashis Biswas

E-Mail Website
Guest Editor
Faculty of Law and Business, Australian Catholic University, 8-20 Napier St, North Sydney, NSW 2060, Australia
Interests: WSN; WBAN; security; privacy; routing; blockchain; e-healthcare; smart health
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad Jabed Morshed Chowdhury

E-Mail Website
Guest Editor
Department of Computer Science and Technology, La Trobe University, Melbourne, VIC 3086, Australia
Interests: blockchain; cyber security; privacy; WSN; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Dr. Shantanu Pal

E-Mail Website
Guest Editor
School of Information Technology, Deakin University, Melbourne, VIC 3125, Australia
Interests: cybersecurity; privacy; blockchain; IoT; WSN; WBAN
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the proliferation of interconnected devices and the Internet of Things (IoT), the vulnerabilities within wireless sensor networks (WSNs) have magnified, making them attractive targets for cyber intrusions. Attacks such as eavesdropping, data injection, and masquerading exploit WSN vulnerabilities. Therefore, a resilient WSN architecture requires ensuring confidentiality, authenticity, and availability. Furthermore, bridging the gap between existing security methods and real-world deployment is essential, necessitating adaptive, practical solutions.

This Special Issue highlights the critical need for comprehensive strategies that ensure data confidentiality, system integrity, and user trust. By delving into the intricate challenges posed by security breaches, erosion of trust, and unauthorized invasions of privacy, this Special Issue strives to shed light on innovative solutions, cutting-edge research, and collaborative efforts that collectively safeguard the future of wireless sensor networks in an increasingly interconnected world. Potential topics include but are not limited to the following:

  • Security aspects and requirements in WSN applications;
  • Advanced WSN authentication techniques;
  • Trust and privacy in WSN systems;
  • Cutting-edge cryptography for WSN security;
  • Cryptanalysis and security attacks in WSN systems;
  • Diverse applications of WSN technology;
  • Overcoming challenges in WSN development;
  • Radio frequency identification (RFID) in WSNs;
  • Blockchain's role in WSN trust;
  • Wireless body area network security and privacy;
  • Deep learning for WSN security insights.

Dr. Kamanashis Biswas
Dr. Mohammad Jabed Morshed Chowdhury
Dr. Shantanu Pal
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

  • security
  • privacy
  • trustworthiness
  • wireless sensor networks
  • Internet of Things

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Published Papers (2 papers)

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Research

24 pages, 2169 KiB  
Article
Automated Sensor Node Malicious Activity Detection with Explainability Analysis
by Md Zubair, Helge Janicke, Ahmad Mohsin, Leandros Maglaras and Iqbal H. Sarker
Sensors 2024, 24(12), 3712; https://doi.org/10.3390/s24123712 - 7 Jun 2024
Cited by 2 | Viewed by 1327
Abstract
Cybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure [...] Read more.
Cybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure safety and security, it is essential to have a reliable system that can automatically detect and prevent any malicious activity, and modern detection systems are created based on machine learning (ML) models. Most often, the dataset generated from the sensor node for detecting malicious activity is highly imbalanced because the Malicious class is significantly fewer than the Non-Malicious class. To address these issues, we proposed a hybrid data balancing technique in combination with a Cluster-based Under Sampling and Synthetic Minority Oversampling Technique (SMOTE). We have also proposed an ensemble machine learning model that outperforms other standard ML models, achieving 99.7% accuracy. Additionally, we have identified the critical features that pose security risks to the sensor nodes with extensive explainability analysis of our proposed machine learning model. In brief, we have explored a hybrid data balancing method, developed a robust ensemble machine learning model for detecting malicious sensor nodes, and conducted a thorough analysis of the model’s explainability. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Sensor Networks (WSNs))
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26 pages, 4146 KiB  
Article
Evaluating Trust Management Frameworks for Wireless Sensor Networks
by Pranav Gangwani, Alexander Perez-Pons and Himanshu Upadhyay
Sensors 2024, 24(9), 2852; https://doi.org/10.3390/s24092852 - 30 Apr 2024
Viewed by 1190
Abstract
Wireless Sensor Networks (WSNs) are crucial in various fields including Health Care Monitoring, Battlefield Surveillance, and Smart Agriculture. However, WSNs are susceptible to malicious attacks due to the massive quantity of sensors within them. Hence, there is a demand for a trust evaluation [...] Read more.
Wireless Sensor Networks (WSNs) are crucial in various fields including Health Care Monitoring, Battlefield Surveillance, and Smart Agriculture. However, WSNs are susceptible to malicious attacks due to the massive quantity of sensors within them. Hence, there is a demand for a trust evaluation framework within WSNs to function as a secure system, to identify and isolate malicious or faulty sensor nodes. This information can be leveraged by neighboring nodes, to prevent collaboration in tasks like data aggregation and forwarding. While numerous trust frameworks have been suggested in the literature to assess trust scores and examine the reliability of sensors through direct and indirect communications, implementing these trust evaluation criteria is challenging due to the intricate nature of the trust evaluation process and the limited availability of datasets. This research conducts a novel comparative analysis of three trust management models: “Lightweight Trust Management based on Bayesian and Entropy (LTMBE)”, “Beta-based Trust and Reputation Evaluation System (BTRES)”, and “Lightweight and Dependable Trust System (LDTS)”. To assess the practicality of these trust management models, we compare and examine their performance in multiple scenarios. Additionally, we assess and compare how well the trust management approaches perform in response to two significant cyber-attacks. Based on the experimental comparative analysis, it can be inferred that the LTMBE model is optimal for WSN applications emphasizing high energy efficiency, while the BTRES model is most suitable for WSN applications prioritizing critical security measures. The conducted empirical comparative analysis can act as a benchmark for upcoming research on trust evaluation frameworks for WSNs. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Sensor Networks (WSNs))
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