• Dr. Devendra Singh

Known as a cyber-physical system (CPS), a cyber-physical system is a network that consists of both cyber and physical components that communicate with one another in a feedback loop. Not only is a CPS required for day-to-day operations, but it is also required for the approval of vital infrastructure, which is the basis for cutting-edge smart devices. The most recent advancements in explainable artificial intelligence have been utilized to assist in the creation of robust intrusion detection systems for use in CPS environments. The objective of this study is to develop an Explainable Artificial Intelligence Enabled Secure Cyber-Physical System Intrusion Detection Technique, which will be referred to as XAIID-SCPS. The identification and classification of intrusions that occur within the CPS platform is the major emphasis of the XAIID-SCPS technique that has been recommended. For the purpose of selecting features, the XAIID-SCPS technique requires the utilization of a Hybrid Enhanced Glowworm Swarm Optimization (HEGSO) algorithm. For the purpose of intrusion detection, the improved Elman Neural Network (IENN) model was utilized, and the Enhanced Fruitfly Optimization (EFFO) approach was utilized to optimize the parameters of the model. In addition, the XAIID-SCPS technique combines the XAI approach LIME in order to enhance the level of comprehension and explainability of the black-box method for intrusion classification that is exact. The results of the simulation demonstrate that the XAIID-SCPS methodology works very well in contrast to other approaches, with a maximum accuracy of 98.87% overall.

security; intrusion detection, cybersecurity , artificial intelligence.

"ENHANCING CYBERSECURITY THROUGH EXPLAINABLE ARTIFICIAL INTELLIGENCE IN INTRUSION DETECTION SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.h137-h153, March-2024, Available :http://www.jetir.org/papers/JETIR2403720.pdf

"ENHANCING CYBERSECURITY THROUGH EXPLAINABLE ARTIFICIAL INTELLIGENCE IN INTRUSION DETECTION SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. pph137-h153, March-2024, Available at : http://www.jetir.org/papers/JETIR2403720.pdf