Improve Intrusion Detection for Decision Tree With Stratified Sampling

This paper aims to improve accuracy of intrusion detection for decision tree algorithm. A number of techniques available for intrusion detection. In this paper, the authors have supervised learning with preprocessing step for intrusion detection. The database is generated using the stratified sampling techniques and the classification algorithm is applied on the samples. The accuracy of proposed model is compared with existing results in order to verify the validity and accuracy of the proposed model.

Provided by: International Journal of Electronics Communication and Computer Engineering Topic: Security Date Added: Oct 2011 Format: PDF

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