The Performance Analysis of Data Mining Algorithms for Anomaly Detection

In this study, performance evaluation of data mining algorithms used to detect harmful computer network traffic is realized. Firstly, feature selection process is performed from the NSL-KDD dataset with different feature selection algorithms. As a result of this process, different datasets are created by combining different attributes. Performans tests are conducted for the detection of anormal traffic using different data mining algorithms on these data sets. As a result of the tests, performance evaluation of different data mining and feature selection algorithms is presented