Hardware Security and Privacy for Cyber-physical Systems
Kinzah Noor, Hasnain Ahmad, Mercy Oka Ebute, Agbotiname Lucky Imoize · River Publishers eBooks · 2025
The current cyber-physical systems (CPSs) face several significant challenges, such as insufficient security consideration in the physical domain, insecure CPS design from the start, attack identification, and survivability limitations. This study analyzes practical applications of industrial robots and wireless medical systems to address these issues. This study provides a generalized CPS that uses an adaptable communications system to control an autonomous multi-robot community. During robotic tasks, the main goal is to provide accurate and almost instantaneous observation of the distant surroundings by digital layer. Our method uses data contraction, downsizing, and dynamic bandwidth control to facilitate successful interaction and joint surveillance operations. The system’s functionality is much improved by this foundation, which makes simultaneous data interchange between digital and real-world counterparts trivial. An enhanced, updated wireless 152 cyber-physical medical system (UWCPMS) is presented that uses machine learning for intrusion recognition and classification to address the abovementioned issues. Deep neural networks are integrated into the proposed system to counteract attacks such as data injection, alteration, and denial of service. Three primary elements comprise the UWCPMS framework: actual time management of resources, computational and security, and connectivity and supervision. It is patient-oriented and enables smartphone-based data control, guaranteeing secure sharing of health information. Our approach proved effective against cyber-physical threats with a reduced computing time of 13 seconds and a 92% detection accuracy.