Smart systems refer to systems that utilise artificial intelligence (AI) algorithms and models, or systems that incorporate smart contracts. With the fast development of AI technology (such as deep learning or reinforcement learning) and blockchain technology, smart systems are increasingly prevalent in all areas of human life, such as finance, health care, agriculture, supply chain, and education.

By incorporating AI and smart contracts, smart systems have many advantages over traditional application systems, such as self-learning, adaptability to new environments, traceability, and immunity. However, such systems have become the targets of many new attacks, which not only causes significant financial damage and potential life loss, but also hinders the large-scale deployment of smart systems in practice. For example, tens of millions of USD have been stolen from several decentralised financial applications due to a vulnerability in their smart contracts which was exploited by hackers. The security of smart application systems is undoubtedly crucial, however, many research questions about this topic have not been answered yet.

This Special Issue aims to collect high-quality research and review articles concerning the attack and defence of smart application systems. We welcome papers investigating the discovery of new vulnerabilities in smart systems, identifying what kind of attacks might be launched to exploit these vulnerabilities, and methods to detect and defend against such attacks, as well as papers looking at forensic techniques to investigate these events and whether any existing techniques (such as program analysis, fuzzing, and generative adversarial networks) can be used.

Potential topics include but are not limited to the following:

• New techniques for defending against attacks on smart systems
• New techniques for discovering vulnerabilities in smart systems
• Case studies of practical and/or new attacks on smart systems
• Secure development of smart systems
• Secure reinforcement of smart systems against attacks
• Digital forensics of security events in smart systems