Securing industry IoT systems with cyber security and fault diagnosis approaches - Lyu, Yuansen (2019)
In this dissertation, the fault diagnosis approaches based on machine learning algorithms are discussed. For industrial processes, faults may be caused by a network attack. In this project, the data packets on the internet will be captured and processed to extract some useful information. Back propagation network and support vector machine are the most popular machine learning algorithms, which have many advantages such as quick and efficient. In the project, lots of historical network data will be trained by the above two algorithms and tested to obtain an optimal fault diagnosis approach.