Advances in Intrusion Detection for IoT Sensor Networks

Dear Colleagues,

The exponential growth of Internet of Things (IoT) sensor networks has enabled large-scale cyber-physical systems across smart cities, critical infrastructure, healthcare, industrial automation, and environmental monitoring. However, the same characteristics that make these systems powerful—massive scale, heterogeneity, decentralization, and resource constraints—also make them highly vulnerable to cyber intrusions.

Traditional intrusion detection systems (IDS), designed for centralized and homogeneous networks, are increasingly ineffective in IoT sensor environments. This has driven rapid advances in data-driven, learning-based, and distributed intrusion detection techniques, particularly those leveraging machine learning and edge intelligence. Despite this progress, significant challenges remain in robustness, scalability, trustworthiness, energy efficiency, and real-world deployment.

This Special Issue aims to present state-of-the-art advances in intrusion detection for IoT sensor networks, covering algorithmic innovations, system architectures, and practical deployments. By embracing a broad yet coherent scope, the Issue seeks to attract high-quality contributions that advance both foundational understanding and applied solutions.

Submissions to this Special Issue may include, but are not limited to, the following topics:

• Intrusion Detection Techniques;
• Architectures and Systems;
• Trustworthiness and Robustness;
• Applications and Case Studies.

Prof. Dr. Tony Jan
Guest Editor

Manuscript Submission Information

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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.