A comprehensive analysis of intrusion detection system in internet of things - Teh, Boon Seong (2020)
This project is a project for academic purpose. Methodology, proposed solution, literature review about the types of intrusion detection system (IDS) will be provided to the student. This project will be illustrating the process of training a model to have the capability to detect malicious traffic packet. To train this model, prototyping is used because the model is upgraded or train with more data to increase its accuracy. The process involved in training a machine learning model consist of four step which is data collect the relevant data, data pre-processing, select the feature and classify. The machine learning classification technique used in this project is mainly decision tree, random forest and naïve bayes. Besides, this project allow student to know more about how IDS works in different network and what are the placement strategy. There are 3 types of network will be mentioned in this project which is wired network, wireless network and ad hoc network. In addition, the placement strategy for IDS includes centralized and distributed. Nonetheless, the most interesting part which is the type of IDS includes signature based IDS, anomaly based IDS, host based IDS and network based IDS. This paper also includes the type of data collection in a normal IDS. The main purpose of this project is to increase the accuracy and reduce fake alerts for an IDS.