The swift development of Artificial Intelligence (AI) has revolutionised various domains, including cybersecurity. However, malevolent actors that use AI for hostile ends have brought forth new challenges. Indeed, defensive AI, which is used by organisations to defend their assets; and offensive AI, which is used by cybercriminals, represent the two sides of this technology. In cybersecurity, AI is used to identify, control, and react to cyber threats. AI facilitates faster threat identification, increases accuracy, and boosts incident response by analysing enormous volumes of data. Nevertheless, when AI is used maliciously to conduct cyberattacks, it is referred to as offensive AI. As AI can scale, adapt, and personalise assaults, cyber criminals use it to make their attacks more effective and difficult to detect.

As more and more devices go online, including smartwatches, smart TVs, smart homes, and smart cars; in addition to the always expanding IoT industry, the attack surface for the Internet of Things grows daily. IoT security is essential for enterprises to safeguard their network infrastructures against IoT device vulnerabilities due to the increased attack surface for security threats. The foundation of IoT security is a cybersecurity approach that guards against cyberattacks on IoT devices and the weak networks they connect to. There is no inherent security in IoT devices. Because IoT devices operate undetected by conventional cybersecurity systems and transmit data over the internet without protection, IoT security is necessary to assist avoid data breaches. In addition to the definition of IoT security, it’s critical to comprehend the various obstacles that businesses must overcome to address IoT security concerns. Security was not a top priority when designing IoT devices. An organisation is more vulnerable to cyberattacks due to the continuous growth and variety of IoT devices and communication channels. The aim of this special issue is to bring together practitioners and researchers who are involved in the design, development, deployment, and exploitation of network security for IoT systems. By discussing the offensive and defensive techniques of AI used for IoT networks, this special issue seeks to encourage cooperation and the creation of fresh concepts and research avenues in this area.

Topics of Interest

The Internet of Things (IoT) offers an extension of the currently offered Internet services. Critical data stream sources in IoT continuously generate enormous volumes of data from a wide range of applications. Therefore, it is crucial to guarantee that the data streams are secure, and resistant to cyberattacks. Indeed, as IoT technology has emerged, cyberattacks have undergone an upgrade in their techniques and tactics, which poses serious threats to the Confidentiality, Integrity and Availability (CIA) of IoT systems. Therefore, various layers of defence should be implemented and trigger defence in depth strategy to mitigate malicious activity in IoT networks. Rapid advancements in offensive AI have made it possible for attackers to initiate complex, extensive campaigns in IoT networks. Defensive AI is a potent counter measure that uses sophisticated algorithms to proactively anticipate, identify, and address these threats in IoT networks. Gaining knowledge about attack risks and impacts in addition to the potential security solutions can help mitigate IoT network vulnerabilities and make the network more resistant to future assaults. This special issue aims to discuss the different offensive and defensive AI techniques that can be exploited in IoT networks. In the age of AI, this special issue seeks to promote creative contributions that tackle present and upcoming cybersecurity issues in IoT networks.

Topics could include and are not limited to:

• AI techniques and approaches for security in IoT networks
• Cyber-attacks on IoT using AI
• Cyber security in IoT using AI
• Risk management in IoT systems and how it leverages AI technology
• Attack techniques and tactics with AI in IoT systems
• Threat detection in IoT networks
• IoT database security