Intrusion Detection Model using Machine Learning Algorithm on Big Data Environment

Recently, the huge amounts of data and its incremental increase have changed the importance of information security and the data analysis systems for a Big Data. Intrusion detection system (IDS) is a system that monitors and also analyzes of the data to detect any intrusion in the system or the network. High volume, variety and also high speed of the data generated in the network have made the data analysis process to detect attacks by traditional techniques very difficult. Big Data techniques are to be used in IDS to deal with the Big Data foraccurate and efficient data analysis process. This paper introduced Spark‑Chi‑SVM model for a intrusion detection. In this model, we have to be used ChiSq Selector for feature selection, and built an intrusion detection model by using support vector machine (SVM) classifier on Apache Spark Big Data platform. We used KDD99 to train and test the model.