Artificial Intelligence vulnerability prevention for closed-loop control system

Akpan, Whyte Asukwo and Orazulume, Chikodili Martha and Essien, Godwin Daniel and Ohaeri, Ifeoma Ugochi and Inyang, Nsikakabasi Nsedu and Chikelu, Peter Okechukwu (2025) Artificial Intelligence vulnerability prevention for closed-loop control system. Global Journal of Engineering and Technology Advances, 23 (2). 025-030. ISSN 2582-5003

Artificial intelligence has created much impact in so many scientific and engineering fields because of its ease, versatility and capability to be adopted to suit different applications. Concerns have arisen for online applications which can be exposed to cyber threats. The various benefits expected to be derived from online application of Artificial intelligence are so huge that these threats cannot be allowed to form a stumbling block to its utilization. Just like many technologies that may usually be faced with some initial challenges in its development and applications, priority should be on how to identify such possible cyber threats and then build up necessary cyber security measures to prevent these threats. It is in this wisdom that this research is focused to offer solutions that will accelerate its safe applications on closed-loop control systems environment. Prevention to AI based control loop vulnerability can be achieved by building strong security controls and zero trust procedures to prevent hackers, intruders, cyber-criminals and blind-cyber wanderers from penetrating into the system either internally or externally. With such protocols which is possible and achievable the objective of application of AI in online closed -loop control system is practicable and will improve the efficiency of the overall system.