IEEE Transactions on Software Engineering - Special issue on computer security and privacy
Neural network system for forecasting method selection
Decision Support Systems
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Data mining with neural networks: solving business problems from application development to decision support
Machine Learning
Error reduction through learning multiple descriptions
Machine Learning
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Improving intrusion detection performance using keyword selection and neural networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on recent advances in intrusion detection systems
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized additive multi-mixture model for data mining
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Is Combining Classifiers Better than Selecting the Best One
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Neuro Fuzzy Systems: Sate-of-the-Art Modeling Techniques
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
A Neural Network Component for an Intrusion Detection System
SP '92 Proceedings of the 1992 IEEE Symposium on Security and Privacy
Agent-Based Hybrid Intelligent Systems
Agent-Based Hybrid Intelligent Systems
Data mining of Bayesian networks using cooperative coevolution
Decision Support Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Data mining approaches for intrusion detection
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Intrusion detection using sequences of system calls
Journal of Computer Security
Evolutionary optimization of radial basis function classifiers for data mining applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Combinations of weak classifiers
IEEE Transactions on Neural Networks
Network intrusion detection system using genetic network programming with support vector machine
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
The use of artificial-intelligence-based ensembles for intrusion detection: a review
Applied Computational Intelligence and Soft Computing
Dynamic learning model update of hybrid-classifiers for intrusion detection
The Journal of Supercomputing
Performance analysis of machine learning algorithms for intrusion detection in MANETs
International Journal of Wireless and Mobile Computing
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Data mining is the use of algorithms to extract the information and patterns derived by the knowledge discovery in databases process. Classification is a very common data mining task. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. Due to increasing incidents of cyber attacks, building effective intrusion detection systems are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. This paper presents two classification methods involving multilayer perceptron and radial basis function and an ensemble of multilayer perceptron and radial basis function. We propose hybrid architecture involving ensemble and base classifiers for intrusion detection systems. The analysis of results shows that the performance of the proposed method is superior to that of single usage of existing classification methods such as multilayer perceptron and radial basis function. Additionally it has been found that ensemble of multilayer perceptron is superior to ensemble of radial basis function classifier for normal behavior and reverse is the case for abnormal behavior. We show that the proposed method provides significant improvement of prediction accuracy in intrusion detection.