SVM for network anomaly detection using ACO feature subset
Over the past short time, network security facing a lot of challenges. Confidentiality, integrity, and availability are the major concerns of the data. To cope with this problem different systems have been developed and the systems are known as Intrusion detection systems. Intrusion detection system...
Saved in:
| Main Authors: | Mehmood, T., Rais, H.B.M. |
|---|---|
| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.30918 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
|
| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995603218&doi=10.1109%2fISMSC.2015.7594039&partnerID=40&md5=241b5ddc489a0a92397d9d3c2bee20f2 http://eprints.utp.edu.my/30918/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Feature selection in intrusion detection, state of the art: A review
by: Rais, H.M., et al.
Published: (2016) -
Enhancement on image face recognition using Hybrid Multiclass SVM (HM-SVM)
by: Selamat, M.H., et al.
Published: (2016) -
Machine learning algorithms in context of intrusion detection
by: Mehmood, T., et al.
Published: (2016) -
Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM
by: Rasheed, W., et al.
Published: (2020) -
ANOMALY DETECTION USING MULTI-INSTANCE ONE-CLASS SVM FOR
MODERATE TRAUMATIC BRAIN INJURY CASES
by: RASHEED, WAQAS
Published: (2019)