Current Perspectives on Internet of Things Security and Intelligent Threat Detection

Abstract

The IoT has revolutionised computing by facilitating the seamless communication of interconnected devices in several industries, including transportation, healthcare, smart cities, and industrial automation. The large-scale deployment of IoT networks has however created a wide range of security and privacy issues, as devices are resource-limited, have diverse architectures, and are facing new types of cyber threats. This review paper provides a general overview of the latest insights into IoT security and intelligent threat detection. It covers the basic security requirements, common vulnerabilities and key attack strategies for IoT environments. Additionally, the paper explores traditional security solutions as well as the latest developments in Malware Detection, Distributed Denial-of-Service (DDoS) attacks, Botnets and Anomalous network behaviour by utilising Machine Learning (ML) and Deep Learning (DL). The algorithms, applications, advantages and disadvantages of intelligent threat detection techniques are highlighted for comparative analysis. The review also presents the summary of the most common public datasets and metrics used for evaluating the performance of different solutions in the field of IoT security studies. Finally, the focus is on key research challenges, emerging technologies, and future directions to support the development of robust, scalable, and intelligent IoT security solutions to address the ever-changing nature of cyber threats.