Cybersecurity in the IoT

Dear Colleagues,

The Internet of things (IoT) comprises a vast number of massively connected devices that deliver intelligent services across many consumer, commercial, and industrial IoT (IIoT) ecosystems. The majority of IoT devices are highly resource-constrained while their security design is in many cases seriously flawed, e.g., by lacking authentication, using hardcoded passwords, or having numerous vulnerabilities, hence rendering the IoT as vulnerable by default. The integration with the cloud creates complex ecosystems that are difficult to analyze, thus contributing to the growing rate and sophistication of cyber-security incidents. The number of attacks utilizing or targeting the cloud has significantly increased, with the next generation of botnets weaponizing both IoT devices and virtual private servers to carry out high-performance attacks. The reduced control/visibility over cloud assets due to their distributed nature and dynamic architecture has led to a considerable increase in supply chain attacks. Such incidents are possible due to the assumption that systems inside the security perimeter are trusted; security approaches, like zero trust, have been proposed as a way to prevent attacks. Taking into consideration these issues, the use of intelligent methods and tools is required to allow for the efficient preparation, prevention, detection, and mitigation of cyber-attacks.

This Special Issue aims to promote the dissemination of the latest methodologies, solutions, and case studies pertaining to IoT cyber-security issues. Its objective is to publish high‐quality articles presenting security algorithms, protocols, frameworks, and solutions for IoT ecosystems. Technical papers describing previously unpublished, original, state‐of‐the‐art research, and not currently under review by a conference or journal, will be considered.

Possible topics of interest of this Special Issue include, but are not limited to:

• Zero-trust architectures for IoT security;
• AI-powered security techniques for IoT;
• Supply-chain IoT security and countermeasures (e.g., device lifecycle management, integrity verification, compliance assessment);
• Big data-driven IoT security methods, including analytics and visualization;
• Disruptive approaches to IoT security (e.g., blockchain, cloud/edge computing, quantum computing);
• Collaborative and distributed paradigms for IoT security;
• Machine/deep learning methods for proactive IoT security (e.g., threat intelligence, behavioral analytics, threat modeling, attack surface reduction);
• Cyber-security in IoT application domains (e.g., smart mobility/cities/agriculture/transporta­tion/grid/maritime).

Prof. Dr. Christos Tryfonopoulos
Prof. Dr. Nicholas Kolokotronis
Guest Editors

Manuscript Submission Information

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• Internet of Things
• cyber-security
• artificial intelligence
• machine/deep learning
• supply chain
• big data