Due to extensive growth of the Internet and increasing availability of tools and methods for intruding and attacking networks, intrusion detection has become a critical component of network security parameters. Intrusion detection in large data is one of the major challenge for the researchers in this area. Anomaly detection using data mining techniques has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks and KDDCUP’99 is the mostly widely used data set for the evaluation of these systems. In this paper we have conducted an comprehensive study and statistical analysis on KDD dataset. We also provide description of features and instances of the dataset. The another important challenge for the researchers in this area is to select an appropriate data mining tool for the analysis. The paper disusses two important and popular tools in this area, weka, Oracle data mining and tanagara. We hope that study carried out in his paper is useful for the reasearcheres in the area of intrusion detection.