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https://www.researchgate.net/publication/3950039_Intrusion_detection_using_neural_networks_and_support_vector_machines
intrusion detection and audit da ta reduction using support v ector machines and neural networks. Using a set of ben chmark data from the KDD (Knowledge Discov ery and Dat a Mining) co mpetition
https://ieeexplore.ieee.org/abstract/document/1007774/
May 17, 2002 · 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.Cited by: 864
https://pdfs.semanticscholar.org/4bef/fcd9c9c768896895918b320b0591a0999ce8.pdf
Mukkamala, Sung 1 Feature Selection for Intrusion Detection using Neural Networks and Support Vector Machines Srinivas Mukkamala1 & Andrew H. Sung1,2 1Department of Computer Science 2Institute for Complex Additive Systems Analysis New Mexico Tech
https://link.springer.com/article/10.1007%2Fs00778-006-0002-5
Aug 31, 2006 · A new intrusion detection system using support vector machines and hierarchical clustering. Authors; Authors and affiliations; ... Artificial neural networks for misuse detection. In: Proceedings of the National Information Systems Security Conference (NISSC98), pp. 443–456. ... Janoski, G., Sung, A.: Intrusion detection: support vector ...Cited by: 432
https://pdfs.semanticscholar.org/eb24/0f463fa57740986a92ee744c3ad75f8228e9.pdf
intrusion detection and audit data reduction using support vector machines and neural networks. Using a set of benchmark data from the KDD (Knowledge Discovery and Data Mining) competition designed by DARPA, we demonstrate that efficient and highly accurate classifiers can be built using either support vector machines (SVMs) or neural networks ...
https://www.researchgate.net/publication/292467230_Network-based_intrusion_detection_with_support_vector_machines
This paper proposes a method of applying Support Vector Machines to network-based Intrusion Detection System (SVM IDS). Support vector machines(SVM) is a learning technique which has been ...
http://www2.cs.uh.edu/~acl/cs6397/Presentation/2003-IEEE-identifying%20important%20features%20for%20ID%20using%20SVM%20and%20NN.pdf
work, support vector machines (SVMs) are found to be superior to neural networks in many important respects of intrusion detection [10,11,12], so we will illustrate feature ranking using SVMs and neural networks. We performed experiments to rank the importance of input features for each of …
https://www.sciencedirect.com/science/article/pii/S0957417410001417
A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering. ... Mukkamala, S., Janoski, G., & Sung, A. (2002). Intrusion detection using neural networks and support vector machines. In: Proceedings of the IEEE international joint ... Intrusion detection with neural networks. Advances in neural information ...Cited by: 446
https://ieeexplore.ieee.org/document/1183050/
Jan 31, 2003 · Identifying important features for intrusion detection using support vector machines and neural networks Abstract: Intrusion detection is a critical component of secure information systems. This paper addresses the issue of identifying important input …
https://www.academia.edu/4990778/Intrusion_detection_using_neural_networks_and_support_vector_machines
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
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