FALSE POSITIVE REDUCTION BY COMBINING SVM AND KNN ALGO

Sushil Kumar Mishra, Pankaj Bhatt

Abstract: With the growth of information technology. There emerges many intrusion detection problem such as cyber security. Intrusion detection system provides basic infrastructure to detect a number of attacks. This research work focuses on intrusion detection problem of network security. The main goal is to detect network behaviour as normal or abnormal. In this research work, two different machine learning algorithm have been combined together to reduce its weakness and takes positive feature of both algorithm. Its experimental results generates better result than other algorithm in terms of performance, accuracy and false positive rate. These combined algorithm has been applied on KDDCUP99 dataset to find better result by improving its performance, accuracy and reducing its false positive rate.

Keywords: Intrusion detection system, KDDCUP99 dataset, False positive rate

DOI: https://doi.org/10.15623/ijret.2015.0402061