Adaptation of Machine Learning and Blockchain Technology in Cyber-Physical System Applications: A Concept Paper

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Abstract

In recent years, Cyber-Physical Systems (CPS) have been adopted in various sectors such as smart cities, smart industries etc. These types of systems continuously generate a huge amount of data which increasingly attract cyber-crimes. There are several existing approaches produced to overcome these issues by using Blockchain Technology (BT) such as Public, Private, Construme, Hybrid Blockchain-based on CPS applications and Machine Learning (ML) such as Support Vector Machine (SVM), Linear Regression, and Decision Tree etc. With the rapid increase in data size affix with cyber-crimes, such approaches become less effective and therefore necessitate the invention of a more robust and self-trainable approach. In this paper, we presented brief details on ML and BT and how they can be adopted in CPS applications to solve security issues concerning cyber-crimes. The architecture was also presented to depict the proposed method. Moreover, technologies/techniques which can be implemented in CPS applications are discovered such as industrial automation, smart buildings, medical systems, and vehicular systems. We also have some future scope and conclusion.

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Abdullahi, M., Alhussian, H., & Aziz, N. (2022). Adaptation of Machine Learning and Blockchain Technology in Cyber-Physical System Applications: A Concept Paper. In Lecture Notes in Electrical Engineering (Vol. 758, pp. 517–523). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-2183-3_48

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