Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Security and Privacy in Wireless Sensor Networks (WSNs)
sensors-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

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 5200

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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

22 pages, 1776 KiB  
Article
Blockchain Integration in UAV Networks: Performance Metrics and Analysis
by Md Imran Hossain, Murat Tahtali, Ugur Turhan and Kamanashis Biswas
Sensors 2024, 24(23), 7813; https://doi.org/10.3390/s24237813 - 6 Dec 2024
Viewed by 840
Abstract
Blockchain technology has revolutionized the management of Unmanned Aerial Vehicle (UAV) networks by enhancing security, enabling decentralized control, and improving operational efficiency. This study assesses the efficiency of private blockchain architectures in UAV networks, specifically examining important performance metrics such as throughput, latency, [...] Read more.
Blockchain technology has revolutionized the management of Unmanned Aerial Vehicle (UAV) networks by enhancing security, enabling decentralized control, and improving operational efficiency. This study assesses the efficiency of private blockchain architectures in UAV networks, specifically examining important performance metrics such as throughput, latency, scalability, and packet size. Furthermore, we evaluate the effectiveness of UAV networks when integrating private blockchain technologies, focusing particularly on key performance indicators such as area, altitude, and data rate. The scope of our work includes extensive simulations that employ a private blockchain to assess its impact on UAV operations. In the blockchain network, throughput decreased as the number of UAVs and transactions increased, while delay remained constant up to a certain point. In contrast, the UAV network saw improved throughput but increased delay with more UAVs and transactions. Changes in area and altitude had little impact on the blockchain network but increased delays in the UAV network. Higher data rates enhanced the UAV network by reducing latency and improving throughput, though this effect was less pronounced in the blockchain network. The aforementioned results highlight the potential and limitations of private blockchains in enhancing the durability and efficiency of UAV networks. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Sensor Networks (WSNs))
►▼ Show Figures

Figure 1

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 3 | Viewed by 1680
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))
►▼ Show Figures

Figure 1

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
Cited by 2 | Viewed by 1524
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))
►▼ Show Figures

Figure 1

Review

Jump to: Research

36 pages, 886 KiB  
Review
Securing IoT Sensors Using Sharding-Based Blockchain Network Technology Integration: A Systematic Review
by Ammad Aslam, Octavian Postolache, Sancho Oliveira and José Dias Pereira
Sensors 2025, 25(3), 807; https://doi.org/10.3390/s25030807 - 29 Jan 2025
Viewed by 468
Abstract
Sharding is an emerging blockchain technology that is used extensively in several fields such as finance, reputation systems, the IoT, and others because of its ability to secure and increase the number of transactions every second. In sharding-based technology, the blockchain is divided [...] Read more.
Sharding is an emerging blockchain technology that is used extensively in several fields such as finance, reputation systems, the IoT, and others because of its ability to secure and increase the number of transactions every second. In sharding-based technology, the blockchain is divided into several sub-chains, also known as shards, that enhance the network throughput. This paper aims to examine the impact of integrating sharding-based blockchain network technology in securing IoT sensors, which is further used for environmental monitoring. In this paper, the idea of integrating sharding-based blockchain technology is proposed, along with its advantages and disadvantages, by conducting a systematic literature review of studies based on sharding-based blockchain technology in recent years. Based on the research findings, sharding-based technology is beneficial in securing IoT systems by improving security, access, and transaction rates. The findings also suggest several issues, such as cross-shard transactions, synchronization issues, and the concentration of stakes. With an increased focus on showcasing the important trade-offs, this paper also offers several recommendations for further research on the implementation of blockchain network technology for securing IoT sensors with applications in environment monitoring. These valuable insights are further effective in facilitating informed decisions while integrating sharding-based technology in developing more secure and efficient decentralized networks for internet data centers (IDCs), and monitoring the environment by picking out key points of the data. Full article
(This article belongs to the Special Issue Security and Privacy in Wireless Sensor Networks (WSNs))
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop