Secure and Intelligent IoT & CPS: AI Driven Attack–Defense, Network Analysis and Smart Data Protection

Dear Colleagues,

The integration of Internet‑of‑Things (IoT) and cyber–physical systems (CPS) with AI is transforming modern infrastructure by enabling cross‑layer communication, intelligent resource allocation and data‑driven decision‑making. At the same time, this convergence creates new vulnerabilities and privacy risks: Industry 4.0 CPS connect sensors, actuators, and cloud services, and this integration exposes networks to emerging cyber threats. Many current security‑by‑design approaches focus only on the design phase and fail to embed mitigation strategies throughout the CPS life cycle. To ensure resilient operation, advanced security technologies, such as machine learning, federated learning, blockchain and digital twins, must be integrated into IoT/CPS, enabling AI‑driven anomaly detection and attack mitigation. Addressing these challenges is essential for advancing optimization, predictive maintenance, intelligent control, and cybersecurity.

This Special Issue invites original research papers, short communications, and review articles that explore how optimization and machine‑learning techniques can safeguard IoT/CPS environments, improve real‑time decision‑making and enhance system intelligence. Topics of interest include the following:

• Secure & Intelligent IoT/CPS Networks: Optimization of wireless protocols and cross‑layer architectures for high‑reliability, low‑latency communication in IoT/CPS, including 5G/6G and time‑sensitive networking (TSN).
• AI‑Driven Autonomy & Control: Machine‑learning techniques for autonomous and adaptive control of CPS components (robots, drones, vehicles) and for network intrusion detection and resilience.
• Smart Data Protection & Privacy: Technologies to protect the integrity and confidentiality of large‑scale data streams. Approaches may include privacy‑preserving analytics (federated learning, differential privacy), cryptographic methods, blockchain‑based integrity assurance, and digital‑twin–assisted resilience to handle the expanded attack surface and safeguard sensitive information.
• Intelligent Sensing & Vision: Advanced AI methods for real‑time defect detection, object recognition, and anomaly sensing in smart environments; leveraging edge computing and private networks for low‑latency processing.
• LLMs for CPS: Development and application of large language models tailored for CPS tasks, including predictive analytics, process optimization, and cross‑domain learning, with emphasis on efficient training and deployment.

Dr. Hansong Xu
Dr. Cheng Qian
Dr. Hengshuo Liang
Guest Editors

Manuscript Submission Information

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