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Abstract: Network Intrusion Detection Systems (NIDSs) have become an important component in network security infrastructure. Currently, many NIDSs are rule-based systems whose performances highly depend on their rule sets. Unfortunately, due to the huge volume of network traffic, coding the rules by security experts becomes difficult and time-consuming. Since data mining techniques can build intrusion detection models adaptively, data mining-based NIDSs have significant advantages over rule-based NIDSs.... (Update)
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BibTeX entry: (Update)
@misc{ and-network,
author = "Jiong Zhang And",
title = "Network Intrusion Detection using Random Forests",
url = "citeseer.ist.psu.edu/748650.html" }
Citations (may not include all citations):107 Principles of Data Mining (context) - Hand, Mannila et al. - 2001
84 Data Mining Approaches for Intrusion Detection - Lee, Stolfo - 1998
18 A Framework for Constructing Features and Models for Intrusi.. - Lee, Stolfo - 2000
16 A Geometric Framework for Unsupervised Anomaly Detection: De.. - Eskin, Arnold et al. - 2002
13 Mining Fuzzy Association Rules and Fuzzy Frequency Episodes .. (context) - Luo, Bridges - 2000 DBLP
11 Random Forests - Breiman - 2001
8 Adaptive Intrusion Detection: A Data Mining Approach - Lee, Stolfo et al. - 2000 DBLP
8 Probability Estimates for Multi-class Classification by Pair.. - Wu, Lin et al. - 2004 ACM
6 Intrusion Detection Techniques for Mobile Wireless Networks - Zhang, Lee et al. - 2003 ACM
4 Improving Intrusion Detection Performance Using Keyword Sele.. - Lippmann, Cunningham - 2000 ACM DBLP
3 Results of the KDD'99 Classifier Learning (context) - Elkan - 2000 ACM DBLP
3 Real Time Data Mining-based Intrusion Detection - Lee, Stolfo et al. - 2001
2 An Application of Machine Learning to Network Intrusion Dete.. (context) - Chris, Lyn - 1999 ACM DBLP
1 Ensemble Learning for Prediction (context) - Popescu, Friedman - 2004
1 IDDM: Intrusion Detection Using Data Mining Techniques (context) - Abraham - 2001
1 The UCI KDD Archive (context) - datasets - 1999
1 ADAM: Detecting Intrusions by Data Mining (context) - Barbarra, Couto et al. - 2001
1 Robust Prediction of Fault-Proneness by Random Forests (context) - Guo, Ma et al. - 2004 ACM
1 High-dimensional Pattern Analysis in Multimedia Information .. (context) - Wu - 2004
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