Securing the Internet of Things: Advances in Attack and Intrusion Detection Mechanisms

Dear Colleagues,

Aims and Scope

The Internet of Things (IoT) has revolutionized modern life by enabling seamless connectivity across devices, industries, and infrastructures. However, the proliferation of IoT devices has also introduced significant security challenges. Due to their resource constraints, heterogeneity, and widespread deployment, IoT systems are particularly vulnerable to a wide range of cyber threats, including denial-of-service (DoS) attacks, spoofing, data exfiltration, and botnet infections.

This Special Issue aims to bring together cutting-edge research and practical solutions focused on attack detection and intrusion prevention in IoT environments. We invite contributions that address the theoretical foundations, algorithmic innovations, and real-world implementations of security mechanisms tailored for IoT systems.

Topics of Interest

Topics include, but are not limited to, the following:

• Machine learning and deep learning approaches for IoT intrusion detection;
• Lightweight and energy-efficient security mechanisms;
• Edge and fog computing-based threat detection;
• Blockchain and distributed ledger technologies for secure IoT;
• Zero-trust architectures in IoT networks;
• Privacy-preserving intrusion detection systems;
• Threat modelling and risk assessment for IoT;
• Secure firmware and software update mechanisms;
• Case studies and real-world deployments of IoT security solutions;
• Adversarial attacks and defenses in IoT environments.

Importance and Relevance

With the rapid expansion of IoT across critical sectors such as healthcare, smart cities, industrial automation, and transportation, ensuring robust security is paramount. This Special Issue will provide a platform for researchers and practitioners to share novel insights and foster collaboration in developing resilient IoT systems. It aligns with the growing demand for secure-by-design IoT architecture and contributes to the advancement of trustworthy computing.

Potential Contributors

We anticipate submissions from leading researchers in cybersecurity, IoT, machine learning, and embedded systems. Potential contributors may include the following:

• Academic researchers from computer science, electrical engineering, and information security;
• Industry professionals working on IoT platforms and cybersecurity solutions;
• Government and defense agencies involved in critical infrastructure protection.

Dr. Morshed Chowdhury
Guest Editor

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