Paper Info
Title
Tool support for the evaluation of anomaly traffic classification for network resilience
Abstract
Resilience is the ability of the network to maintain an acceptable level of operation in the face of anomalies, such as malicious attacks, operational overload or misconfigurations. Techniques for anomaly traffic classification are often used to characterize suspicious network traffic, thus supporting anomaly detection schemes in network resilience strategies. In this paper, we extend the PReSET toolset to allow the investigation, comparison and analysis of algorithms for anomaly traffic classification based on machine learning. PReSET was designed to allow the simulation-based evaluation of resilience strategies, thus enabling the comparison of optimal configurations and policies for combating different types of attacks (e.g., DDoS attacks, worms) and other anomalies. In such resilience strategies, policies written in the Ponder2 language can be used to activate/reconfigure traffic classification modules and other mechanisms (e.g., traffic shaping), depending on monitored results in the simulation environment. Our results show that PReSET can be a valuable tool for network operators to evaluate anomaly traffic classification techniques in terms of standard performance metrics.
Year
DOI
Venue
2015
10.1109/ISCC.2015.7405566
2015 IEEE Symposium on Computers and Communication (ISCC)
Keywords
Field
DocType
anomaly traffic classification evaluation,network resilience,anomaly traffic classification techniques,network resilience strategy,PReSET toolset,machine learning,simulation-based evaluation,Ponder2 language
Traffic classification,Psychological resilience,Data mining,Anomaly detection,Denial-of-service attack,Computer science,Analysis of algorithms,Computer network,Feature extraction,Operator (computer programming),Traffic shaping
Conference
Citations 
PageRank 
References 
0
0.34
11
Authors
5
Name
Order
Citations
PageRank
Anderson Santos da Silva1202.85
Juliano Araujo Wickboldt219821.08
Alberto E. Schaeffer Filho312220.30
Angelos K. Marnerides47415.89
Andreas Mauthe550752.28