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Cybersecurity for Sensor Technologies

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

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2131

Special Issue Editors


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Guest Editor
Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Spain
Interests: pattern recognition; data management; privacy; cybersecurity; recommender systems; smart health; supply chain and blockchain
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Informatics, University of Piraeus, 80 Karaoli & Dimitriou Str., 18534 Piraeus, Greece
Interests: cryptography; computer security; privacy; blockchain

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Guest Editor
Smart Health Research Group, Department of Computer Engineering and Maths, Universitat Rovira i Virgili, Tarragona, Spain
Interests: smart health; cognitive health; data privacy; ubiquitous computing and AI (artificial intelligence)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors, both software and hardware, are becoming an indispensable part of modern infrastructures. They are highly interconnected and seamlessly integrated into diverse platforms, coming closer to what we call IoT, realizing Smart Cities and Ubiquitous Computing. According to their sensing capabilities and application context, each sensor or sensing infrastructure requires specific design and features resulting in the evolution of fog and edge computing. However, the inspiring opportunities offered by fostering fully controlled ubiquitous contexts do not come without a cost.

Sensing technologies are known to face challenges related to data management, performance, energy consumption, and communication, among others. Those challenges are often exploited, along with other context-specific ones, with malicious intents to, e.g., exfiltrate sensitive information, and perform cyber-physical attacks. Sensing technologies are prone to cyberattacks, which may have a different impact according to the technology used and their underlying platform, and may require divergent protection and prevention mechanisms. The latter problem requires an interdisciplinary approach due to the existing heterogeneous components, technologies, and implementations.

In this Special Issue of Sensors, we invite submissions focusing on Cybersecurity for Sensor Technologies. We welcome submissions that offer relevant advancements towards sensing technologies and their protection, along with the prevention and detection of cyber threats. We expect contributions to automated data analytics and intelligent systems to secure sensing technologies, particularly based on intelligent and automated solutions, as well as disruptive technologies such as blockchain and federated platforms. Of particular interest are papers focusing on the particular challenges of context-aware environments (e.g., Industry 4.0, smart cities, healthcare, vehicular networks and drones), where sensing technologies are becoming prevalent.

Potential topics may include:

  • Intrusion detection and prevention.
  • Biometrics security, including access control and authentication technologies.
  • Attack methods, including adversarial machine learning.
  • Intelligent trust management, security and privacy protocols for sensing technologies.
  • Data analytics and automated policy enforcement for securing sensing technologies.
  • Monitoring and securing resources in sensing technologies.
  • Forensic analysis and readiness of sensors, both hardware and software.
  • Collaborative and cognitive frameworks to secure heterogeneous sensing technologies.
  • Securing context-aware environments and applications (e.g., smart cities including civil infrastructures, healthcare-related contexts, Industry 4.0 and IoT, vehicular sensor networks and drones).
  • Secure and/or privacy-preserving aggregation.
  • Use of Trusted Execution Environments for securing sensors.
  • Secure fog and edge computing.

Dr. Fran Casino
Dr. Constantinos Patsakis
Dr. Agusti Solanas
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

  • intrusion detection
  • biometrics security
  • privacy protocols
  • automated data analytics
  • disruptive technologies
  • secure fog/edge computing

Published Papers (1 paper)

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Research

20 pages, 5194 KiB  
Article
Interaction of Secure Cloud Network and Crowd Computing for Smart City Data Obfuscation
by Manikandan Thirumalaisamy, Shajahan Basheer, Shitharth Selvarajan, Sara A. Althubiti, Fayadh Alenezi, Gautam Srivastava and Jerry Chun-Wei Lin
Sensors 2022, 22(19), 7169; https://doi.org/10.3390/s22197169 - 21 Sep 2022
Cited by 14 | Viewed by 1467
Abstract
There can be many inherent issues in the process of managing cloud infrastructure and the platform of the cloud. The platform of the cloud manages cloud software and legality issues in making contracts. The platform also handles the process of managing cloud software [...] Read more.
There can be many inherent issues in the process of managing cloud infrastructure and the platform of the cloud. The platform of the cloud manages cloud software and legality issues in making contracts. The platform also handles the process of managing cloud software services and legal contract-based segmentation. In this paper, we tackle these issues directly with some feasible solutions. For these constraints, the Averaged One-Dependence Estimators (AODE) classifier and the SELECT Applicable Only to Parallel Server (SELECT-APSL ASA) method are proposed to separate the data related to the place. ASA is made up of the AODE and SELECT Applicable Only to Parallel Server. The AODE classifier is used to separate the data from smart city data based on the hybrid data obfuscation technique. The data from the hybrid data obfuscation technique manages 50% of the raw data, and 50% of hospital data is masked using the proposed transmission. The analysis of energy consumption before the cryptosystem shows the total packet delivered by about 71.66% compared with existing algorithms. The analysis of energy consumption after cryptosystem assumption shows 47.34% consumption, compared to existing state-of-the-art algorithms. The average energy consumption before data obfuscation decreased by 2.47%, and the average energy consumption after data obfuscation was reduced by 9.90%. The analysis of the makespan time before data obfuscation decreased by 33.71%. Compared to existing state-of-the-art algorithms, the study of makespan time after data obfuscation decreased by 1.3%. These impressive results show the strength of our methodology. Full article
(This article belongs to the Special Issue Cybersecurity for Sensor Technologies)
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