Accuracy Improvement of IDS via Filter Parallelization

Maryam Amanifar, DR. Mohammad Saniee Abadeh


Daily increase in using the computer network and internet technology services from one hand and attacking the computer networks from other hand which has caused the Intrusion Detection Systems (IDS) become a very important part of the computer system immunity. It has also become an important field of research in the computer system networks. Until now, many different approaches to enhance the applicability of IDSs are presented such as Machine Learning and Data Mining. In this paper an approach for enhancing the accuracy in the IDSs is presented. In order to compare the applicability of this approach with earlier presented approaches, a set of similar data KDD99 have been used. SVM classifier and K-NN have been used to detect intrusion with high classification rate.

Keywords: IDS; K-NN; SVM; KDD99

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