Distributed representation of fuzzy rules and its application to pattern classification
Fuzzy Sets and Systems
Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Three objective genetics-based machine learning for linguisitc rule extraction
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Finding fuzzy classification rules using data mining techniques
Pattern Recognition Letters
Using Artificial Anomalies to Detect Unknown and Known Network Intrusions
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Results of the KDD'99 classifier learning
ACM SIGKDD Explorations Newsletter
A Neural Network Component for an Intrusion Detection System
SP '92 Proceedings of the 1992 IEEE Symposium on Security and Privacy
Anomaly detection of web-based attacks
Proceedings of the 10th ACM conference on Computer and communications security
Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
Intrusion detection using a fuzzy genetics-based learning algorithm
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
Intrusion detection using sequences of system calls
Journal of Computer Security
Incorporating soft computing techniques into a probabilistic intrusion detection system
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An artificial immune system architecture for computer securityapplications
IEEE Transactions on Evolutionary Computation
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
Hybridization of fuzzy GBML approaches for pattern classification problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolutionary computing for knowledge discovery in medical diagnosis
Artificial Intelligence in Medicine
IEEE Transactions on Fuzzy Systems
Automatic network intrusion detection: Current techniques and open issues
Computers and Electrical Engineering
A novel intrusion detection system based on feature generation with visualization strategy
Expert Systems with Applications: An International Journal
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The capability of fuzzy systems to solve different kinds of problems has been demonstrated in several previous investigations. Genetic fuzzy systems (GFSs) hybridize the approximate reasoning method of fuzzy systems with the learning capability of evolutionary algorithms. The objective of this paper is to design and analysis of various kinds of genetic fuzzy systems to deal with intrusion detection problem as a new real-world application area which is not previously tackled with GFSs. The resulted intrusion detection system would be capable of detecting normal and abnormal behaviors in computer networks. We have presented three kinds of genetic fuzzy systems based on Michigan, Pittsburgh and iterative rule learning (IRL) approaches to deal with intrusion detection as a high-dimensional classification problem. Experiments were performed with DARPA data sets which have information on computer networks, during normal and intrusive behaviors. The paper presents some results and compares the performance of different generated fuzzy rule sets in detecting intrusion in a computer network according to three different types of genetic fuzzy systems.