Collaborative Filtering and Random Forest Classification Algorithm for PROBE Attacks Detection in a Network Classification
During the past few years huge amount of network attacks have been increased the requirement of efficient network intrusion detection techniques for detecting attacks. In the existing approach, different classification techniques are used for identifying various real time network attacks using data mining. However, most of the algorithms fail to classify the different types of attacks due to absence of collaborative filtering technique and robust classifiers. In proposed system Robust collaborating filter Algorithm is an optimization method used for fine-tuning of the features whereas Random Forest(RF), a highly accurate classifier, is designed here for Probe kinds of attacks classification.