Advanced Sensing and Intelligent Technologies for Cybersecurity in the Internet of Things Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 10 November 2025 | Viewed by 716
Special Issue Editor
Special Issue Information
Dear Colleagues,
The rapid expansion of Internet of Things (IoT) technologies has significantly changed modern industries by improving connectivity and automation across various sectors. The IoT has facilitated innovative applications and increased efficiency, but it has also introduced new vulnerabilities and potential points of attack. The growing complexity of these systems, especially when combined with cyber-physical systems and critical infrastructure, has resulted in significant security gaps, making them attractive targets for advanced cyberattacks.
Traditional cybersecurity solutions often struggle to address the specific challenges posed by IoT systems, such as limited resources, scalability issues, and heterogeneity. However, advancements in sensing technologies, edge and fog computing, decentralized architectures, and large language models (LLMs) have enabled new opportunities for IoT security.
This Special Issue aims to encourage research on state-of-the-art sensing and intelligent technologies that enhance the detection, prevention, and mitigation of cybersecurity threats in IoT networks.
We welcome technical contribution papers, industrial case studies, and review articles that focus on innovative strategies for identifying and addressing threats in IoT environments. Topics of interest include, but are not limited to, the following research areas:
- Advanced sensing techniques for secure IoT;
- Advanced sensing technologies for intrusion and anomaly detection;
- Machine learning, AI-driven methods, and large language models (LLMs) for sensor-based anomaly detection in IoT systems;
- Real-time monitoring and threat detection frameworks;
- Security architectures based on edge and fog computing;
- Decentralized trust establishment and reputation systems;
- Large language models (LLMs) for threat intelligence, vulnerability assessment, and automated responses in IoT and CPS;
- Multimodal sensing;
- Privacy-preserving methods for sensor data in IoT networks;
- Adversarial machine learning in sensor-driven IoT security systems;
- Blockchain for IoT cyber security;
- Socio-technical solutions for IoT cyber security.
Dr. Mohammed Al-Mhiqani
Guest Editor
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