Detecting Denial of Service Message Flooding Attacks in SIP based Services

Document Type : Research Article

Authors

1 Zoha Asgharian graduated from computer engineering school of Iran University of Science and Technology, Tehran, Iran (email: z_asgharian@comp.iust.ac.ir)

2 Corresponding Author, Hassan Asgharian is PhD student in computer engineering school of Iran University of Science and Technology, Tehran, Iran (email: asgharian@iust.ac.ir)

3 Ahmad Akbari is an associate professor in the computer engineering school of Iran University of Science and Technology, Tehran, Iran (email: Akbari@iust.ac.ir)

4 Bijan Raahemi is with University of Ottawa, Canada (email: raahemi@iust.ac.ir)

Abstract

Increasing the popularity of SIP based services (VoIP, IPTV, IMS infrastructure) lead to concerns about its ‎security. The main signaling protocol of next generation networks and VoIP systems is Session Initiation Protocol ‎‎(SIP). Inherent vulnerabilities of SIP, misconfiguration of its related components and also its implementation ‎deficiencies cause some security concerns in SIP based infrastructures. New attacks are developed that target ‎directly the underlying SIP protocol in these related SIP setups. To detect such kinds of attacks we combined ‎anomaly-based and specification-based intrusion detection techniques. We took advantages of the SIP state machine ‎concept (according to RFC 3261) in our proposed solution. We also built and configured a real test-bed for SIP ‎based services to generate normal and assumed attack traffics. We validated and evaluated our intrusion detection ‎system with the dump traffic of this real test-bed and we also used another specific available dataset to have a more ‎comprehensive evaluation. The experimental results show that our approach is effective in classifying normal and ‎anomaly traffic in different situations. The Receiver Operating Characteristic (ROC) analysis is applied on final ‎extracted results to select the working point of our system (set related thresholds). ‎
 

Keywords


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