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Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities
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Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities

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 (20 October 2024) | Viewed by 13570

Special Issue Editor

Dr. Grzegorz Kołaczek

E-Mail Website
Guest Editor
Faculty of Information and Communication Technology, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
Interests: cybersecurity; threat intelligence; cybersecurity of big data; cybersecurity of AI; cyber–physical cybersecurity; anonymity and confidentiality; distributed systems; anomaly detection; novelty discovery

Special Issue Information

Dear Colleagues,

The purpose of this Special Issue is to present the latest research results in the field of cybersecurity and IoT systems. We encourage the publication of original research and review articles on various aspects of IoT and cybersecurity. Topics of interest include, but are not limited to, the design and implementation of secure IoT systems, the application of machine learning and artificial intelligence to IoT security, privacy issues in IoT, and the development of new IoT security protocols and standards. In addition, other related topics such as IoT security architectures, protocols and standards, IoT security assessment, testing and verification, IoT security management, monitoring and auditing, IoT security analytics, forensics and incident response, IoT security applications and case studies in various fields such as smart cities, healthcare, transportation, and energy, and IoT security challenges and opportunities in emerging technologies such as artificial intelligence, blockchain, edge computing, and 5G are also welcome.

In this Special Issue, we encourage submissions of articles that propose innovative solutions to enhance IoT device and network security, mitigate threats, and protect user privacy. Research that provides insight into the current state of IoT security is also welcome.

The goal of this publication is to provide the knowledge necessary to address cybersecurity challenges, while enabling readers to take advantage of the opportunities offered by IoT technologies.

Dr. Grzegorz Kołaczek
Guest Editor

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

  • IoT security
  • IoT privacy
  • machine learning for IoT security
  • secure IoT architectures and protocols
  • IoT security assessment and testing
  • IoT security applications and case studies
  • IoT security challenges and opportunities in emerging technologies

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Published Papers (8 papers)

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Editorial

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5 pages, 149 KiB  
Editorial
Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities
by Grzegorz Kołaczek
Appl. Sci. 2025, 15(6), 2935; https://doi.org/10.3390/app15062935 - 8 Mar 2025
Viewed by 989
Abstract
The continuous development and increasing availability of Internet of Things (IoT) solutions have led to an era of connectivity in which everyday objects—from household appliances to industrial machines—are connected via the Internet [...] Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)

Research

Jump to: Editorial

42 pages, 2740 KiB  
Article
We Are Not Equipped to Identify the First Signs of Cyber–Physical Attacks: Emotional Reactions to Cybersecurity Breaches on Domestic Internet of Things Devices
by Sanja Budimir, Johnny R. J. Fontaine, Nicole M. A. Huijts, Antal Haans, Wijnand A. IJsselsteijn, Anne-Marie Oostveen, Frederic Stahl, Ryan Heartfield, George Loukas, Anatolij Bezemskij, Avgoustinos Filippoupolitis, Ivano Ras and Etienne B. Roesch
Appl. Sci. 2024, 14(24), 11855; https://doi.org/10.3390/app142411855 - 18 Dec 2024
Cited by 1 | Viewed by 1330
Abstract
The increasing number of domestic Internet of Things (IoT) devices in our lives leads to numerous benefits, but also comes with an increased risk of cybersecurity breaches. These breaches have psychological consequences for the users. We examined the nature of the psychological impact [...] Read more.
The increasing number of domestic Internet of Things (IoT) devices in our lives leads to numerous benefits, but also comes with an increased risk of cybersecurity breaches. These breaches have psychological consequences for the users. We examined the nature of the psychological impact of cybersecurity breaches on domestic IoT by investigating emotional experiences in a scenario study (Study 1) and a field experiment (Study 2) using the five emotion components of the Component Process Model (CPM) and emotion regulation as a framework. We replicated a three-dimensional structure for emotional experiences found in a previous study, with an addition of an ancillary fourth dimension in the second study. The first dimension represents emotional intensity. The second bipolar dimension describes constructive vs. unconstructive action tendencies. On the third dimension, also bipolar, cognitive and motivational emotion features are opposed to affective emotion features. The fourth dimension, labeled distress symptoms, mainly reflects negative emotions. In Study 2, most of the introduced frequent irregularities on IoT devices were not noticed, and the intensity of emotional reactions and tendencies to react in a constructive way decreased throughout the phases of the experiment. These findings reveal that we are not emotionally equipped to identify potential threats in the cyber world. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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26 pages, 1829 KiB  
Article
Securing the Future of Web-Enabled IoT: A Critical Analysis of Web of Things Security
by Khalied M. Albarrak
Appl. Sci. 2024, 14(23), 10867; https://doi.org/10.3390/app142310867 - 23 Nov 2024
Cited by 2 | Viewed by 1396
Abstract
The Web of Things (WoT) represents a significant advancement on the Internet of Things (IoT), where web technologies are integrated to enhance device interoperability and accessibility. While this integration offers numerous benefits, it also introduces new and complex security challenges. This paper presents [...] Read more.
The Web of Things (WoT) represents a significant advancement on the Internet of Things (IoT), where web technologies are integrated to enhance device interoperability and accessibility. While this integration offers numerous benefits, it also introduces new and complex security challenges. This paper presents a critical analysis of WoT security, examining the ecosystem’s vulnerabilities and associated threats. Our contributions include an in-depth analysis of existing threat enumeration methodologies, highlighting misconceptions and inefficiencies that may weaken security measures. We further conduct a comprehensive survey of critical threats within the WoT environment, detailing potential attack vectors and misuses linked to these threats. To address these security gaps, we propose a set of defenses tailored to each identified threat, providing a holistic view of the WoT’s security landscape. We also develop abstract architectural models of the WoT using UML, serving as foundational tools for understanding the interactions and risks within WoT systems. Finally, we model a specific attack scenario, demonstrating how attacks unfold in real-world WoT environments and the importance of defense strategies. These findings aim to guide the development of secure WoT systems, ensuring robust defenses against evolving security threats. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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26 pages, 1192 KiB  
Article
Vulnerability and Attack Repository for IoT: Addressing Challenges and Opportunities in Internet of Things Vulnerability Databases
by Anna Felkner, Jan Adamski, Jakub Koman, Marcin Rytel, Marek Janiszewski, Piotr Lewandowski, Rafał Pachnia and Wojciech Nowakowski
Appl. Sci. 2024, 14(22), 10513; https://doi.org/10.3390/app142210513 - 14 Nov 2024
Cited by 1 | Viewed by 2008
Abstract
The article’s primary purpose is to highlight the importance of cybersecurity for Internet of Things (IoT) devices. Due to the widespread use of such devices in everyone’s daily and professional lives, taking care of their security is essential. This security can be strengthened [...] Read more.
The article’s primary purpose is to highlight the importance of cybersecurity for Internet of Things (IoT) devices. Due to the widespread use of such devices in everyone’s daily and professional lives, taking care of their security is essential. This security can be strengthened by raising awareness about the vulnerabilities and risks of these devices among their manufacturers and users. Therefore, this paper shows the results of several years of work regarding building vulnerabilities and exploiting databases, with a particular focus on IoT devices. We highlight multiple unique features of our solution, such as aggregation, correlation, and enrichment of known vulnerabilities and exploits collected from 12 different sources, presentation of a timeline of threats, and combining vulnerability information with exploits. Our databases have more than 300,000 entries, which are the result of aggregating and correlating more than 1,300,000 entries from 12 different databases simultaneously, enriched with information from unstructured sources. We cover the innovative utilization of Artificial Intelligence (AI) to support data enrichment, examining the usage of the Light Gradient-Boosting Machine (LGBM) model to automatically predict vulnerability severity and Mistral7B to categorize vulnerable products, which, especially in the case of IoT devices, is critical due to the diversity of nomenclature. Social media and various unstructured sources are prominent places for gathering information. Retrieving data from them is much more complex than from structured databases, but the information there is normally supplied at a faster rate. Thus, we added Mastodon monitoring to enhance our threat timelines. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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15 pages, 311 KiB  
Article
PUF and Chaotic Map-Based Authentication Protocol for Underwater Acoustic Networks
by Qi Xie and Ye Yao
Appl. Sci. 2024, 14(13), 5400; https://doi.org/10.3390/app14135400 - 21 Jun 2024
Cited by 3 | Viewed by 920
Abstract
A secure and effective authentication and communication scheme between users and underwater sensors plays an important role in improving the detection and utilization of marine resources in underwater acoustic networks (UANs). However, due to the energy limitations and susceptibility to capture of underwater [...] Read more.
A secure and effective authentication and communication scheme between users and underwater sensors plays an important role in improving the detection and utilization of marine resources in underwater acoustic networks (UANs). However, due to the energy limitations and susceptibility to capture of underwater sensors and gateways, it is necessary to design a lightweight authentication protocol that can resist capture of sensors and gateways during attacks. In this paper, a lightweight authentication protocol for UANs based on the Physical Unclonable Function (PUF) and chaotic map is proposed. We used the advantages of PUF to resist sensors and gateways being captured in attacks and the chaotic map to achieve lightweight authentication because the computational cost of the chaotic map is almost one-third that of Elliptic Curve Cryptography (ECC). Additionally, we used the formal security proof in the random oracle model to prove the security of the proposed scheme. Our scheme was more secure and efficient compared with some other related schemes in terms of security and performance requirements, and the proposed scheme is suitable for UANs. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
35 pages, 9178 KiB  
Article
Lightweight, Trust-Managing, and Privacy-Preserving Collaborative Intrusion Detection for Internet of Things
by Aulia Arif Wardana, Grzegorz Kołaczek and Parman Sukarno
Appl. Sci. 2024, 14(10), 4109; https://doi.org/10.3390/app14104109 - 12 May 2024
Cited by 12 | Viewed by 2465
Abstract
This research introduces a comprehensive collaborative intrusion detection system (CIDS) framework aimed at bolstering the security of Internet of Things (IoT) environments by synergistically integrating lightweight architecture, trust management, and privacy-preserving mechanisms. The proposed hierarchical architecture spans edge, fog, and cloud layers, ensuring [...] Read more.
This research introduces a comprehensive collaborative intrusion detection system (CIDS) framework aimed at bolstering the security of Internet of Things (IoT) environments by synergistically integrating lightweight architecture, trust management, and privacy-preserving mechanisms. The proposed hierarchical architecture spans edge, fog, and cloud layers, ensuring efficient and scalable collaborative intrusion detection. Trustworthiness is established through the incorporation of distributed ledger technology (DLT), leveraging blockchain frameworks to enhance the reliability and transparency of communication among IoT devices. Furthermore, the research adopts federated learning (FL) techniques to address privacy concerns, allowing devices to collaboratively learn from decentralized data sources while preserving individual data privacy. Validation of the proposed approach is conducted using the CICIoT2023 dataset, demonstrating its effectiveness in enhancing the security posture of IoT ecosystems. This research contributes to the advancement of secure and resilient IoT infrastructures, addressing the imperative need for lightweight, trust-managing, and privacy-preserving solutions in the face of evolving cybersecurity challenges. According to our experiments, the proposed model achieved an average accuracy of 97.65%, precision of 97.65%, recall of 100%, and F1-score of 98.81% when detecting various attacks on IoT systems with heterogeneous devices and networks. The system is a lightweight system when compared with traditional intrusion detection that uses centralized learning in terms of network latency and memory consumption. The proposed system shows trust and can keep private data in an IoT environment. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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17 pages, 1119 KiB  
Article
Improvement of a Conditional Privacy-Preserving and Desynchronization-Resistant Authentication Protocol for IoV
by Qi Xie and Juanjuan Huang
Appl. Sci. 2024, 14(6), 2451; https://doi.org/10.3390/app14062451 - 14 Mar 2024
Cited by 6 | Viewed by 1346
Abstract
In Internet of Vehicles (IoV), the secure data transmission between vehicles and transportation infrastructure effectively ensures the safety and fast driving of vehicles, while authentication and key agreement protocols between vehicles and transportation infrastructure (V2I) play an important role in ensuring data security [...] Read more.
In Internet of Vehicles (IoV), the secure data transmission between vehicles and transportation infrastructure effectively ensures the safety and fast driving of vehicles, while authentication and key agreement protocols between vehicles and transportation infrastructure (V2I) play an important role in ensuring data security and user privacy. However, how to design a provably secure and lightweight V2I authentication protocol for IoV is a challenge. Recently, Kumar et al. proposed a conditional privacy-preserving and desynchronization-resistant authentication protocol for IoV, but we find that Kumar et al.’s scheme is vulnerable to identity guessing attacks, impersonation attacks, and a lack of session key secrecy once the attacker obtains data stored in smart card through side-channel attacks. We also point out that Kumar et al.’s protocol is vulnerable to Roadside Unit (RSU) captured attacks and lacks perfect forward secrecy. Therefore, we propose an improved V2I authentication protocol for IoV, which uses the Physical Unclonable Function (PUF) to resist RSU captured attacks, and designed a three-factor secrecy strategy to resist side-channel attacks; a conditional privacy-preserving strategy was also adopted to achieve anonymity and malicious user tracking. Furthermore, the proposed protocol is provably secure under the random oracle model and has low computation and communication costs. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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17 pages, 4621 KiB  
Article
Securing Internet of Things Applications Using Software-Defined Network-Aided Group Key Management with a Modified One-Way Function Tree
by Antony Taurshia, Jaspher W. Kathrine, J. Andrew and Jennifer Eunice R
Appl. Sci. 2024, 14(6), 2405; https://doi.org/10.3390/app14062405 - 13 Mar 2024
Cited by 3 | Viewed by 1214
Abstract
Group management is practiced to deploy access control and to ease multicast and broadcast communication. However, the devices that constitute the Internet of Things (IoT) are resource-constrained, and the network of IoT is heterogeneous with variable topologies interconnected. Hence, to tackle heterogeneity, SDN-aided [...] Read more.
Group management is practiced to deploy access control and to ease multicast and broadcast communication. However, the devices that constitute the Internet of Things (IoT) are resource-constrained, and the network of IoT is heterogeneous with variable topologies interconnected. Hence, to tackle heterogeneity, SDN-aided centralized group management as a service framework is proposed to provide a global network perspective and administration. Group management as a service includes a group key management function, which can be either centralized or decentralized. Decentralized approaches use complex cryptographic primitives, making centralized techniques the optimal option for the IoT ecosystem. It is also necessary to use a safe, scalable approach that addresses dynamic membership changes with minimal overhead to provide a centralized group key management service. A group key management strategy called a one-way Function Tree (OFT) was put forth to lower communication costs in sizable dynamic groups. The technique, however, is vulnerable to collusion attacks in which an appending and withdrawing device colludes and conspires to obtain unauthorized keys for an unauthorized timeline. Several collusion-deprived improvements to the OFT method are suggested; however, they come at an increased cost for both communication and computation. The Modified One-Way Function Tree (MOFT), a novel technique, is suggested in this proposed work. The collusion resistance of the proposed MOFT system was demonstrated via security analysis. According to performance studies, MOFT lowers communication costs when compared to the original OFT scheme. In comparison to the OFT’s collusion-deprived upgrades, the computation cost is smaller. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities)
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