Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic

Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic

Network anomaly detection and classification is an important open issue in network security. Several approaches and systems based on different mathematical tools have been studied and developed, among them, the Anomaly-Network Intrusion Detection System (A-NIDS), which monitors network traffic and c...

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Bibliographic Details
Main Authors: Jayro Santiago-Paz, Deni Torres-Roman, Angel Figueroa-Ypiña, Jesus Argaez-Xool
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:Entropy
Subjects:
generalized entropies
network traffic
anomaly detection
OC-SVM
Mahalanobis kernel
Mahalanobis distance
non-Gaussian data
Online Access:http://www.mdpi.com/1099-4300/17/9/6239

Internet

http://www.mdpi.com/1099-4300/17/9/6239

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