Abstract

In order to improve the detection of intrusion detection rate and lower false detection rate, and put forward a kind of attribute reduction based on a semi-supervised fuzzy clustering method, and applied to the intrusion detection, first of all select the samples of data preprocessing, use a semi-supervised fuzzy clustering to reduce sample, with the reduction algorithm based on attribute dependence. Finally, reduction was carried out on the sample set. Simulation experiments using KDD99 data set, the text results show that the detection has higher efficiency.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.