• RITU BALA
• Dr. RITU NAGPAL

Intrusion detection system is a very important part of our defense system which is used to identify the abnormal activities. As the number of attacks occurring in our computer network is increasing day by day and this is why It has become very important to detect the intrusion, intercept and analyze a large number of network data. Normally, traditional IDS relies on the extensive information of our security experts. To reduce this dependency, different machine learning and data mining techniques are used. In this paper we will compare the performance of different learning algorithm like decision tree, naïve bayes, multilayer perception using different datasets such as KDDCup99, NSL-KDD and by different scenarios identify between normal and abnormal connections on different data sets

intrusion detection system, data mining, KDDCup, NSL-KDD, naïve bayes, machine learning

"Analysis of KDDCUP99 and NSL-KDD using Various Classification Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.919-923, December-2018, Available :http://www.jetir.org/papers/JETIR1810A36.pdf

"Analysis of KDDCUP99 and NSL-KDD using Various Classification Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp919-923, December-2018, Available at : http://www.jetir.org/papers/JETIR1810A36.pdf