State Transition Analysis: A Rule-Based Intrusion Detection Approach
IEEE Transactions on Software Engineering
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Intrusion Detection
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Network Intrusion Detection: An Analyst's Handbook
Network Intrusion Detection: An Analyst's Handbook
A Statistical Method for Profiling Network Traffic
Proceedings of the Workshop on Intrusion Detection and Network Monitoring
Validating an Online Adaptive System Using SVDD
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Support Vector Data Description
Machine Learning
A study in using neural networks for anomaly and misuse detection
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
A new intrusion detection system using support vector machines and hierarchical clustering
The VLDB Journal — The International Journal on Very Large Data Bases
Immune system approaches to intrusion detection --- a review
Natural Computing: an international journal
Data description and noise filtering based detection with its application and performance comparison
Expert Systems with Applications: An International Journal
Statistical Techniques for Network Security: Modern Statistically-Based Intrusion Detection and Protection
Intrusion Detection Technology Based on SVDD
ICINIS '09 Proceedings of the 2009 Second International Conference on Intelligent Networks and Intelligent Systems
Intrusion detection of DoS/DDoS and probing attacks for web services
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
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This paper presents a novel approach to describe the normal behavior of computer networks (as used in IDS) based on Support Vector Data Description (SVDD). In the proposed method we find a minimal hyper-ellipse around the normal objects in the input space. Hyper-ellipse can be expanded in high dimensional space (ESVDD) or to be used as a preprocessing in SVDD method (PESVDD) to obtain better results for IDS. KDD-cup99 has been used as data set for test of the proposed method. The overall experiments show prominence of our work in comparison with similar previous works.