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Cybersecurity in Sensor Networks

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

Deadline for manuscript submissions: 30 April 2025 | Viewed by 1631

Special Issue Editors


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Guest Editor
Cyber Security and Networks, School of Computing, Engineering and Built Environment (SCEBE), Glasgow Caledonian University, Glasgow G4 0BA, UK
Interests: computer vision; machine learning; cyber security and networks
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK
Interests: network protocols; wireless; mobile and sensor networks; performance modelling and evaluation of parallel and distributed systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a Call for Papers for a Special Issue on Cyber Security in Sensor Networks. This Special Issue aims to bring together researchers, practitioners, and experts to share their latest findings, innovative ideas, and significant advancements in the field of cyber security as it pertains to sensor networks. Our goal is to foster a collaborative and comprehensive exploration of the current challenges, emerging trends, and cutting-edge solutions in securing sensor networks, and to provide a platform for disseminating high-quality research that can drive further developments and applications in this area. 

Scope and Topics

Sensor networks are integral to many critical applications, including environmental monitoring, healthcare, smart cities, home and industrial automation, disaster management and response, and energy management. Ensuring the security of these networks is paramount to protect sensitive data and maintain the integrity and availability of services.

This Special Issue, entitled “Cyber Security in Sensor Networks”, seeks high-quality, original research papers, case studies, and review articles on various aspects of cybersecurity in sensor networks.

Topics of interest include, but are not limited to, the following:

  • Threat Detection and Mitigation;
  • Intrusion Detection Systems;
  • Secure Communication Protocols;
  • Analysis of network and security protocols;
  • Cryptographic Solutions;
  • Privacy Protection;
  • Authentication and Access Control;
  • Network Security;
  • IoT Security;
  • Resource-Constrained Security Solutions;
  • Cyber-Physical Systems Security
  • Unmanned System Security for Vehicles
  • Machine Learning for Security;
  • Sensor network data fusion and data aggregation;
  • IoT including: IoMT, IoFT and IoD, IIOT;
  • Wireless body area network (WBAN).

Dr. Salaheddin Hosseinzadeh
Dr. Alireza Shahrabi
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

  • sensor networks
  • sensor networks security
  • cyber–physical systems security
  • cyber threats and attacks
  • applications of AI for cybersecurity

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Published Papers (1 paper)

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Research

33 pages, 5782 KiB  
Article
MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud
by Noah Oghenefego Ogwara, Krassie Petrova, Mee Loong (Bobby) Yang and Stephen G. MacDonell
Sensors 2025, 25(3), 670; https://doi.org/10.3390/s25030670 - 23 Jan 2025
Viewed by 1151
Abstract
Mobile cloud computing (MCC) is a technological paradigm for providing services to mobile device (MD) users. A compromised MD may cause harm to both its user and to other MCC customers. This study explores the use of machine learning (ML) models and stochastic [...] Read more.
Mobile cloud computing (MCC) is a technological paradigm for providing services to mobile device (MD) users. A compromised MD may cause harm to both its user and to other MCC customers. This study explores the use of machine learning (ML) models and stochastic methods for the protection of Android MDs connected to the mobile cloud. To test the validity and feasibility of the proposed models and methods, the study adopted a proof-of-concept approach and developed a prototype system named MINDPRESS. The static component of MINDPRES assesses the risk of the apps installed on the MD. It uses a device-based ML model for static feature analysis and a cloud-based stochastic risk evaluator. The device-based hybrid component of MINDPRES monitors app behavior in real time. It deploys two ML models and functions as an intrusion detection and prevention system (IDPS). The performance evaluation results of the prototype showed that the accuracy achieved by the methods for static and hybrid risk evaluation compared well with results reported in recent work. Power consumption data indicated that MINDPRES did not create an overload. This study contributes a feasible and scalable framework for building distributed systems for the protection of the data and devices of MCC customers. Full article
(This article belongs to the Special Issue Cybersecurity in Sensor Networks)
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