Bio-Medical and Cyber-Physical Systems Intrusion Detection System

Proceedings of The 5th International Conference on Research in Humanities

Year: 2022

DOI:

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Bio-Medical and Cyber-Physical Systems Intrusion Detection System

Ajay Kaushik, V. Samuel Raj

 

ABSTRACT: 

The industrial sector has made the shift from embedded systems to cyber-physical systems (CPSs) with the introduction of Industry 4.0 and the Internet of Things (IoT). Manufacturers may now use data collected from on-board sensors to monitor the operation of industrial equipment. Industrial systems may be monitored in this way, and abnormalities can be identified. As the quantity of visible data grows, many firms are forced to explore for new ways to deal with such vast volumes of data. Time detection of intrusion in industrial and commercial data has emerged as essential enablers for satisfying the scientific community’s current expectations for CPSs and bio-medical devices in recent years. Big data technology might be used to build a platform for CPS real-time monitoring at work. This research provides a Bio-medical and CPS-Intrusion Detection System built with Apache Spark (CPS-IDS). Using real-world datasets, the proposed technique is verified. This system’s effectiveness, as well as its suitability and scalability for future demand, are evaluated in a real-world situation. The overall efficiency of the equipment has enhanced as a result of this method.

keywords: Artificial Intelligence, Cyber Security, Cyber Dataset, Machine Learning, IoT.