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Internet of Things Security: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 9716

Special Issue Editors


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Guest Editor
Department of Computer Science, Abdul Wali Khan University, Mardan, Pakistan
Interests: Internet of Things; security; blockchain; artificial intelligence; cloud/edge computing; wireless sensor network; quality of service
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Technology Business and Arts, University of Suffolk, Ipswich, UK
Interests: wireless sensor networks; Internet of Things; blockchain; machine learning; security

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Guest Editor
School of Information Technology, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, Victoria, VIC 3220, Australia
Interests: Internet of Things; cyber security; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Information Systems and Business Intelligence, Peter Faber Business School, Australian Catholic University, Sydney, NSW, Australia
Interests: artificial intelligence; machine learning; decision support system; Internet of Things; fuzzy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internet of Things (IoT) devices are becoming ubiquitous while IoT services are becoming pervasive. The applications of IoT in various sectors is increasing exponentially, which has given rise to new and ingenious adversarial threats against these application in general, and the devices in particular. Cyber-attacks and their applications are not new to our virtual world, but as IoT devices are deeply interwoven in our society, it is extremely important to come up with new security measures which are different and superior to the existing ones. This is mainly because the nature of data exchanged by IoT devices is different and hence the threats posed to the data are unique. Thus, novel and sophisticated security measures and techniques are needed which can help us safeguard critical infrastructure from these malicious threats posed by malevolent entities to the emerging applications of IoT.

Our aim is to collect high-quality papers relevant to the scope of this Special Issue. We encourage researchers from various fields within the journal’s scope to contribute papers highlighting the latest developments in their research field relating to IoT security, and to invite relevant experts and colleagues to do so. Topics of interest for this Special Issue include, but are not limited to:

  • Novel theories, concepts, and architecture for securing the IoT
  • New privacy challenges in intelligent IoT devices
  • Efficient cryptography for intelligent IoT devices
  • Secure data integrity and validation techniques for intelligent IoT devices
  • Security threat detection theories and technologies for intelligent IoT devices
  • Blockchains and smart contracts for IoT
  • ML/DL-based solutions for securing IoT applications
  • Novel security measures for cloud/edge-enabled IoT applications

Dr. Mian Ahmad Jan
Dr. Syed Rooh Ullah Jan
Dr. Adnan Anwar
Dr. Walayat Hussain
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. Applied Sciences 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 2400 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

  • Internet of Things, security
  • privacy
  • blockchain
  • machine/deep learning

Published Papers (5 papers)

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Research

21 pages, 2577 KiB  
Article
Enhancing Energy Efficiency by Improving Internet of Things Devices Security in Intelligent Buildings via Niche Genetic Algorithm-Based Control Technology
by Rui Liang, Yalong Xing and Linhui Hu
Appl. Sci. 2023, 13(19), 10717; https://doi.org/10.3390/app131910717 - 26 Sep 2023
Cited by 2 | Viewed by 2484
Abstract
The security measures of IoT devices used in intelligent buildings are one of the ways by which energy efficiency can be accomplished. IoT devices are very important for data collecting and monitoring in intelligent buildings, but a lack of security could result in [...] Read more.
The security measures of IoT devices used in intelligent buildings are one of the ways by which energy efficiency can be accomplished. IoT devices are very important for data collecting and monitoring in intelligent buildings, but a lack of security could result in errors in energy consumption decisions that result in energy waste. To ensure the success of the control systems used for energy optimization, it is necessary to address the security of IoT devices in order to avoid illegal access, data manipulation, and disruptions. This work proposes a research idea and scheme for energy-saving optimization of intelligent buildings by assuring the security of IoT devices used in intelligent buildings. First of all, we defined several parameters that are related to IoT devices’ security, energy consumption, and occupant comfort in the intelligent building environment. Secondly, we collected data for each of these parameters by utilizing IoT devices such as actuators, sensors, and other control systems. The niche genetic algorithm (NGA) refers to a particular class of genetic algorithms that is used to tackle problems involving many optimization objectives. We focused on optimizing both energy consumption and occupants’ comfort; therefore, we used an NGA for the preprocessed data with the goal of evaluating the data for the purpose of ensuring the comfort of occupants and protection of the security of IoT devices, which eventually leads to energy optimization. Finally, the results of the proposed approach are analyzed and carefully compared with earlier work, demonstrating that our proposed approach is significantly more effective and energy-optimized than earlier approaches. The results show that the total power consumption of the intelligent building system after using our proposed model is generally reduced by more than 18% compared with that before optimization, which shows that the intelligent building system-adaptive optimization control model can effectively optimize the operating parameters of the energy-saving system and achieve the security of IoT devices. Full article
(This article belongs to the Special Issue Internet of Things Security: Latest Advances and Prospects)
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21 pages, 1114 KiB  
Article
Blockchain-Based Distributed Computing Consistency Verification for IoT Mobile Applications
by Jiahao Zhao, Yushu Zhang and Jiajia Jiang
Appl. Sci. 2023, 13(13), 7762; https://doi.org/10.3390/app13137762 - 30 Jun 2023
Viewed by 840
Abstract
The maturation of wireless connectivity, blockchain (distributed ledger technologies), and intelligent systems has fostered a comprehensive ecosystem for the Internet of Things (IoT). However, the growing volume of data generated by IoT devices creates substantial pressure on blockchain storage and computation capabilities, impeding [...] Read more.
The maturation of wireless connectivity, blockchain (distributed ledger technologies), and intelligent systems has fostered a comprehensive ecosystem for the Internet of Things (IoT). However, the growing volume of data generated by IoT devices creates substantial pressure on blockchain storage and computation capabilities, impeding the further development of the IoT ecosystem. Decentralizing data storage across multiple chains and utilizing cross-chain technology for data exchange eliminates the need for expensive centralized infrastructure, lowers data transfer costs, and improves accessibility. Hence, the issue of computational and storage pressure in blockchain can be improved. Nonetheless, the data of IoT devices are constantly updating, and ensuring consistency for dynamic data across heterogeneous chains remains a significant challenge. To address the aforementioned challenge, we propose a blockchain-based distributed and lightweight data consistency verification model (BDCA), which leverages a batch verification dynamic Merkle hash tree (BV-MHT) and an advanced gamma multi-signature scheme (AGMS) to enable consistent verification of dynamic data while ensuring secure and private data transmission. The AGMS scheme is reliable and robust based on security analysis while the dependability and consistency of BDCA are verified through inductive reasoning. Experimental results indicate that BDCA outperforms CPVPA and Fortress in communication and computation overhead for data preprocessing and auditing in a similar condition, and the AGMS scheme exhibits superior performance when compared to other widely adopted multi-signature schemes such as Cosi, BLS, and RSA. Furthermore, BDCA provides up to 99% data consistency guarantees, demonstrating its practicality. Full article
(This article belongs to the Special Issue Internet of Things Security: Latest Advances and Prospects)
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17 pages, 633 KiB  
Article
Sensing and Device Neighborhood-Based Slot Assignment Approach for the Internet of Things
by Mushtaq Khan, Rahim Khan, Nadir Shah, Abdullah Ghani, Samia Allaoua Chelloug, Wasif Nisar and Jason Teo
Appl. Sci. 2023, 13(8), 4682; https://doi.org/10.3390/app13084682 - 7 Apr 2023
Viewed by 1183
Abstract
Concurrent communication constitutes one of the challenging issues associated with IoT networks, as it is highly likely that multiple devices may start communication simultaneously. This issue has become more complex as devices belonging to the IoT networks increasingly become mobile. To resolve this [...] Read more.
Concurrent communication constitutes one of the challenging issues associated with IoT networks, as it is highly likely that multiple devices may start communication simultaneously. This issue has become more complex as devices belonging to the IoT networks increasingly become mobile. To resolve this issue, various mechanisms have been reported in the literature. However, none of these approaches has considered the neighborhood information of a server module to resolve this issue. In this paper, a neighborhood-based smart slot allocation scheme for the IoT is presented where member devices are mobile. In this scheme, every CH or server module is bound to maintain two different types of slots, i.e., dedicated and reserved. Dedicated slots are assigned to every device on a First-Come-First-Serve (FCFS) basis, whereas reserved slots are assigned to the migrated devices. Additionally, as long as a device Ci is located inside the server module’s coverage area, it is required to use these dedicated slots. Simulation results verified that the proposed neighborhood-based slot allocation scheme performed better than existing approaches and considerably improved various performance metrics, such as 20% in lifetime, 27.8% in slot allocation, and 30.50% in slot waiting time. Full article
(This article belongs to the Special Issue Internet of Things Security: Latest Advances and Prospects)
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27 pages, 5985 KiB  
Article
Towards Mitigating Jellyfish Attacks Based on Honesty Metrics in V2X Autonomous Networks
by Messaoud Benguenane, Ahmed Korichi, Bouziane Brik and Nadjet Azzaoui
Appl. Sci. 2023, 13(7), 4591; https://doi.org/10.3390/app13074591 - 5 Apr 2023
Viewed by 1834
Abstract
In vehicle-to-everything (V2X) networks, security and safety are inherently difficult tasks due to the distinct characteristics of such networks, such as their highly dynamic topology and frequent connectivity disruptions. Jellyfish attacks are a sort of denial of service attack that are challenging to [...] Read more.
In vehicle-to-everything (V2X) networks, security and safety are inherently difficult tasks due to the distinct characteristics of such networks, such as their highly dynamic topology and frequent connectivity disruptions. Jellyfish attacks are a sort of denial of service attack that are challenging to deal with, since they conform to protocol norms while impairing network performance, particularly in terms of communication overhead and reliability. Numerous existing approaches have developed new techniques with which to identify and prevent these attacks; however, no approach has been capable of facing all three types of Jellyfish attacks, which include reordering attacks, delay variance attacks, and periodic drop attacks. In this work, we design a new protocol that analyzes the behavior of every node in a network and selects the trusted routes for data transmission to their intended destination by calculating different Honesty metrics. The OMNET++ simulator was used to evaluate the overall performance of the proposed protocol. Various evaluation metrics, such as the packet delivery ratio, end-to-end delay, and throughput, are considered and compared with other existing approaches. Full article
(This article belongs to the Special Issue Internet of Things Security: Latest Advances and Prospects)
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14 pages, 3341 KiB  
Article
Power Distribution IoT Tasks Online Scheduling Algorithm Based on Cloud-Edge Dependent Microservice
by Ruolin Chen, Qian Cheng and Xinhui Zhang
Appl. Sci. 2023, 13(7), 4481; https://doi.org/10.3390/app13074481 - 1 Apr 2023
Cited by 2 | Viewed by 1247
Abstract
The power distribution network business gradually extends from the grid domain to the social service domain, and the new business keeps expanding. The edge device uses microservice architecture and container technology to realize the processing of different services by one physical device. Although [...] Read more.
The power distribution network business gradually extends from the grid domain to the social service domain, and the new business keeps expanding. The edge device uses microservice architecture and container technology to realize the processing of different services by one physical device. Although the power distribution network IoT with cloud-edge architecture has good scalability, scenarios with insufficient resources for edge devices may occur. In order to support the scheduling and collaborative processing of tasks under the resource-constrained scenario from the edge device, this paper proposes a cloud-edge collaborative online scheduling method for the distribution of station area tasks under the microservice architecture. The article models the characteristics of power tasks and their constraints in the cloud-edge containerized scenario, designs the priority policy and task assignment policy based on the cloud-edge scheduling mechanism of containerized power tasks, and schedules the tasks in real time by an improved online algorithm. Simulation results show that the algorithm proposed in this paper has high task execution efficiency, can improve the completion rate of important tasks with limited resources of edge devices, and improves system security through resource replacement. Full article
(This article belongs to the Special Issue Internet of Things Security: Latest Advances and Prospects)
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