Machine Learning Algorithms for Cybersecurity in IoT Networks

Dear Colleagues,

The Internet of Things (IoT) is a rapidly growing field that involves the interconnectivity of physical devices, sensors, and software. These interconnected devices generate massive amounts of data that can be analyzed to improve efficiency, productivity, and safety. As a result, cybersecurity has become a critical issue for the protection of sensitive information in IoT networks. Machine learning algorithms have emerged as a powerful tool to identify and prevent cyberattacks in IoT networks. They offer a way to detect and prevent attacks in real time, and they can also be used to analyze large volumes of data to identify patterns and anomalies.

This Special Issue will focus on the application of machine learning algorithms for cybersecurity in IoT networks. We will explore the latest research and developments in this rapidly evolving field. Some of the topics that will be covered include:

• Machine learning-based intrusion detection systems for IoT networks;
• Deep learning techniques for malware detection in IoT networks;
• Use of artificial intelligence for anomaly detection in IoT networks;
• Machine learning-based approaches for secure communication in IoT networks;
• Detection and prevention of DDoS attacks using machine learning in IoT networks;
• Machine learning techniques for risk assessment in IoT networks;
• Secure data analytics in IoT networks using machine learning algorithms;
• Use of machine learning algorithms for IoT network security monitoring;
• Deep learning-based approaches for detecting zero-day attacks in IoT networks;
• Machine learning-based techniques for secure authentication in IoT networks.

The articles in this Special Issue demonstrate the wide range of applications of machine learning techniques for cybersecurity in IoT networks, including smart cities, healthcare, agriculture, and energy management.

This Special Issue will bring together researchers and practitioners from academia, industry, and governments to share their insights, ideas, and experiences on the use of machine learning algorithms for cybersecurity in IoT networks. The goal is to provide a comprehensive overview of the state-of-the-art in this field and to identify future research directions and challenges.

Dr. Adel Abusitta
Dr. Ziad Kobti
Guest Editors

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• IoT security
• IoT anomaly detection
• artificial intelligence for security in IoT