Improve Intrusion Detection for Decision Tree with Stratified Sampling

Devendra kailashiya; Kanak Saxena

The present paper aims to improve accuracy of intrusion detection for decision tree algorithm. A number of techniques available for intrusion detection. In this paper we have supervised learning with preprocessing step for intrusion detection. The database is generated i 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.

Select Volume / Issues:

• Volume 2 Issue 2, Oct. 2011

Year:

2011

Type of Publication:

Article

Keywords:

Intrusion Detection; Decision Tree; Stratified Sampling; ID3; preprocessing and classification

Journal:

IJECCE

Volume:

2

Number:

2

Pages:

62-66

Month:

October