Network Security White Papers
A New Intrusion Detection System Using Support Vector Machines and Hierarchical Clustering
Overview Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network services by purposely occupying or sabotaging network resources and services. This can be done by sending large amounts of network traffic, exploiting well-known faults in networking services, and by overloading network hosts. The interest here is in anomaly detection and the proposed method is a scalable solution for detecting network-based anomalies. Support Vector Machines (SVM) is used for classification. This paper presents a study for enhancing the training time of SVM, specifically when dealing with large data sets, using hierarchical clustering analysis.
| Publisher | Springer Science+Business Media | File Format | |
|---|---|---|---|
| Date Published | August 2006 | ||
| Format | White Papers | ||
| Topics | |||
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