Lightweight and Decentralized Artificial Intelligence for Secure Smart Systems and Cyber-Physical Networks
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "AI Systems: Theory and Applications".
Deadline for manuscript submissions: 30 June 2027 | Viewed by 185
Editors
Interests: cybersecurity in IoT and IIoT; machine learning (ML) for intrusion detection system (IDS); wireless networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid deployment of smart systems, Industrial Internet of Things (IIoT), CPS, autonomous systems and edge computing has revolutionized the modern industrial and societal infrastructure. Such smart systems are continuously generating huge amounts of diverse data sets, while needing real-time, dependable and secure decision-making with certain computational, communication and energy constraints. Centralized AI approaches face many challenges, such as privacy issues, restricted bandwidth, scalability problems and susceptibility to cyberattacks. Therefore, there is a need for lightweight and decentralized AI approaches to support smart systems. The recent developments in edge intelligence, federated learning, split learning, distributed optimization, continuous learning, TinyML, neuromorphic computing and AI safety have greatly enhanced the abilities of decentralized intelligent systems. On the other hand, the increasing complexity of cybersecurity risks that include adversarial machine learning, data poisoning, model inversion, denial-of-service attacks, ransomware and zero-day attacks has emphasized the necessity to develop AI models that are accurate, resilient, interpretable, adaptive and efficient. The objective of this Special Issue is to provide an overview of the recent advances in theory, algorithms, architecture and applications of lightweight and decentralized AI to ensure the security of smart systems and cyber-physical networks. The research that combines artificial intelligence with cybersecurity, edge computing, Industrial Internet of Things, wireless communication, digital twin technology and autonomous systems will be considered for publication.
Prof. Dr. Adel Ali Ahmed
Prof. Dr. Anton Satria Prabuwono
Guest Editors
Manuscript Submission Information
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Keywords
- lightweight machine learning
- decentralized intelligence
- cybersecurity
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