• G.Meghana Madhuri
• Dr.D.Vivekananda Reddy

An Intrusion Detection System is a module of the software that monitors the activities occurring in a computer system or network. An intruder tries to modify the packets or fabricate the malicious packets and insert them into a set of network flows on the network. It has the capability of detecting attacks which compromise the confidentiality, integrity or availability of network resources. The proposed method uses Supervised Learning In Quest (SLIQ), a fast scalable decision tree classifier for intrusion detection. NSL-KDD Dataset is used to study effectiveness of the classification method. Accuracy metric is considered as performance metric for the proposed method. The objective of this paper is to inspect the packets in the network flow using SLIQ and to predict whether the flow is malicious or normal flow.

Intrusion Detection System (IDS), Supervised Learning in Quest (SLIQ), Gini Index, NSL KDD Dataset, Netbeans IDE.

"Intrusion Detection System using Gini Index Based Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.684-687, November-2020, Available :http://www.jetir.org/papers/JETIR2011092.pdf

"Intrusion Detection System using Gini Index Based Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp684-687, November-2020, Available at : http://www.jetir.org/papers/JETIR2011092.pdf