Title
Improving Accuracy for Intrusion Detection through Layered Approach Using Support Vector Machine with Feature Reduction
Abstract
Digital information security is the field of information technology which deal with all about identification and protection of information. Whereas, identification of the threat of any Intrusion Detection System (IDS) in the most challenging phase. Threat detection become most promising because rest of the IDS system phase depends on the solely on \"what is identified\". In this view, a multilayered framework has been discussed which handles the underlying features for the identification of various attack (DoS, R2L, U2R, Probe). The experiments validates the use SVM with genetic approach is efficient.
Year
DOI
Venue
2016
10.1145/2909067.2909100
Proceedings of the ACM Symposium on Women in Research 2016
DocType
ISBN
Citations 
Conference
978-1-4503-4278-0
1
PageRank 
References 
Authors
0.36
1
3
Name
Order
Citations
PageRank
Aditi Nema110.36
Basant Tiwari210.36
Vivek Tiwari32971391.08