Paper Info
Title
Application of evolutionary algorithms in detection of SIP based flooding attacks
Abstract
The Session Initiation Protocol (SIP) is the de facto standard for user's session control in the next generation Voice over Internet Protocol (VoIP) networks based on the IP Multimedia Subsystem (IMS) framework. In this paper, we first analyze the role of SIP based floods in the Denial of Service (DoS) attacks on the IMS. Afterwards, we present an online intrusion detection framework for detection of such attacks. We analyze the role of different evolutionary and non-evolutionary classifiers on the classification accuracy of the proposed framework. We have evaluated the performance of our intrusion detection framework on a traffic in which SIP floods of varying intensities are injected. The results of our study show that the evolutionary classifiers like sUpervised Classifier System (UCS) and Genetic clASSIfier sySTem (GAssist) can even detect low intensity SIP floods in realtime. Finally, we formulate a set of specific guidelines that can help VoIP service providers in customizing our intrusion detection framework by selecting an appropriate classifier-depending on their requirements in different service scenarios.
Year
DOI
Venue
2009
10.1145/1569901.1570092
GECCO
Keywords
Field
DocType
evolutionary classifier,proposed framework,different service scenario,session initiation protocol,sip flood,evolutionary algorithm,low intensity sip flood,online intrusion detection framework,internet protocol,intrusion detection framework,voip service provider,genetics,service provider,voice over internet protocol,intrusion detection,dos attack,ip multimedia subsystem,denial of service,network security
De facto standard,Denial-of-service attack,Computer science,Network security,Computer network,Service provider,Session Initiation Protocol,IP Multimedia Subsystem,Intrusion detection system,Voice over IP
Conference
Citations 
PageRank 
References 
24
0.95
12
Authors
2
Name
Order
Citations
PageRank
M. Ali Akbar1291.92
Muddassar Farooq2122183.47