Effective Framework of J48 Algorithm using Semi-Supervised Approach for Intrusion Detection

Abstract

Network security is a very important aspect for internet enabled systems. As the internet keeps developing the number of security attacks as well as their severity has shown a significant increase. The Intrusion Detection System (IDS) plays a very important role in discovering anomalies and attacks in the network. The aim of an intrusion detection system is to identify those entities that attempt to destabilize security controls that have been put in place. The field of machine learning is rapidly gaining more attention in the development of these intrusion detection systems. Machine learning techniques can be broadly classified into three broad categories: Supervised, Un-supervised and semi-supervised. The supervised learning method displays good classification accuracy for those attacks that are aready known to us. But this method requires a large amount of training data.The availability of labelled data is not only time consuming but also very expensive. The evolving field of semi-supervised learning offers a promising direction for supplementary research. Hence, in this paper we propose a semi-supervised approach for a pattern based IDS to improve performance and to reduce the false alarm rate. The experimentation is performed on KDD CUP99 dataset and we use the J48 Algorithm in order to implement the semi-supervised learning.

Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations

“…The proposed approach integrated SSL into LLE to utilize the labeled data. The studies reported in [51,186,193] have shown that semi-supervised approaches can perform better than supervised and unsupervised approaches for conventional network intrusion detection, but these studies are yet to make their way through to IDS for ICS.…”

Early prediction of systemic lupus erythematosus using hybrid K-Means J48 decision tree algorithm

“…Finally, the research highlights the causes of lupus and the method to predict the disease in advance and to extend the life span of the patients. By processing the data with K-means [4,5] and J48 algorithm [6,7] has castoff to predict lupus in advance.…”