With the continuous evolution and wide application of communication technology, network technology, and computing technology, a ubiquitous network environment has been formed, including the Internet, Internet of Things (IoT), and other heterogeneous interconnections. Ubiquitous networks have the characteristics of openness, heterogeneity, and mobility, and can provide diverse and personalized information services at different levels, helping realize the interconnection of all things and the intercommunication of wisdom.

Ubiquitous networks re deeply integrated with the industrial economy, connecting people, machines, things, and systems, which is then called the ubiquitous industrial Internet of Things (IIoT). Many new manufacturing and service systems covering the whole industry chain and the whole value chain have been built, which are regarded as an important foundation of the fourth industrial revolution. Due to the openness, heterogeneity, mobility, and dynamics of the ubiquitous industrial Internet of Things, there exist numerous threats. Information security technologies, such as identity authentication, access control, auditing, situational awareness, and malicious code monitoring, need to be able to identify the risks and threats posed by the above features, so as to update the security policies in time. Traditional information security methods struggle to meet the requirements of ubiquitous networks in terms of diversity, heterogeneity, dynamics, mobility, and openness. Therefore, a series of dynamic and adaptive intelligent defense technologies based on machine learning methods have recently attracted widespread attention.

The aim of this Special Issue is to discuss intelligent defense models, technologies, and applications based on machine learning in the ubiquitous IIoT. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Malicious code intelligent countermeasure techniques in IIoT
• Risk adaptive access control and dynamic access control methods based on machine learning methods in the ubiquitous IoT
• Ubiquitous network attack and defense techniques based on deep learning models
• Automatic generation techniques for access control policy in IIoT
• Access control methods based on smart contracts in IoT block chains
• Intelligent identity authentication techniques in 5G networks
• Automated role engineering methods based on machine learning
• Ubiquitous network intelligent intrusion detection techniques based on machine learning
• Software reverse engineering and malicious code detection methods based on machine learning
• Advances in intrusion detection, information fusion, resource allocation, and optimal scheduling of new cyber-physical systems, such as Internet of Vehicles (IoV) and ubiquitous power Internet of Things