Proceedings ArticleDOI
Intrusion detection using neural networks and support vector machines
Srinivas Mukkamala,Guadalupe I. Janoski,Andrew H. Sung +2 more
- Vol. 2, pp 1702-1707
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TLDR
Using a set of benchmark data from a KDD (knowledge discovery and data mining) competition designed by DARPA, it is demonstrated that efficient and accurate classifiers can be built to detect intrusions.Abstract:
Information security is an issue of serious global concern. The complexity, accessibility, and openness of the Internet have served to increase the security risk of information systems tremendously. This paper concerns intrusion detection. We describe approaches to intrusion detection using neural networks and support vector machines. The key ideas are to discover useful patterns or features that describe user behavior on a system, and use the set of relevant features to build classifiers that can recognize anomalies and known intrusions, hopefully in real time. Using a set of benchmark data from a KDD (knowledge discovery and data mining) competition designed by DARPA, we demonstrate that efficient and accurate classifiers can be built to detect intrusions. We compare the performance of neural networks based, and support vector machine based, systems for intrusion detection.read more
Citations
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A comprehensive survey on machine learning for networking: evolution, applications and research opportunities
Raouf Boutaba,Mohammad A. Salahuddin,Noura Limam,Sara Ayoubi,Nashid Shahriar,Felipe Estrada-Solano,Felipe Estrada-Solano,Oscar Mauricio Caicedo +7 more
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A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering
TL;DR: Experimental results on the KDD CUP 1999 dataset show that the proposed new approach, FC-ANN, outperforms BPNN and other well-known methods such as decision tree, the naive Bayes in terms of detection precision and detection stability.
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An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.
Proceedings ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.