Data Mining Based Classification Technique for Adaptive Intrusion Detection System using Machine learning

[摘要] An intrusion detection system is activity that observe a network or system activities for malicious activities. IDS comes in various variant and the main goal of detecting suspicious traffic in wide variety of ways. There are network based and host based intrusion detection systems.  An intrusion detection system is the process for identifying attacks on network.  Intrusion detection system is categorized into two types: Anomaly based and misuse based detection. The   data mining techniques make it possible to observe the network and seperate from the intruders such as machine learning. Different researcher works for the detection of intrusion on network. In this NSL KDD dataset is used a source of classification.  The main aim  is to recognize signature pattern of known attacks with better detection rate.

[学科分类] 建筑学

[关键词] Clustering;external validation;stability;indices of agreement