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| Content Provider | ACM Digital Library |
|---|---|
| Author | Akbar, M. Ali Farooq, Muddassar |
| Abstract | Real-time Transport Protocol (RTP) is a widely adopted standard for transmission of multimedia traffic in Internet telephony (commonly known as VoIP). Therefore, it is a hot potential target for imposters who can launch different types of Denial of Service (DoS) attacks to disrupt communication; resulting in not only substantive revenue loss to VoIP operators but also undermining the reliability of VoIP infrastructure. The major contribution of this paper is an online framework -- RTP-Miner -- that detects RTP fuzzing attacks in realtime; as a result, it is not possible to deny access to legitimate users. RTP-Miner can detect both header and payload fuzzing attacks. Fuzzing in the header of RTP packets is detected by combining well known distance measures with a decision tree based classifier. In comparison, payload fuzzing is detected through a novel Markov state space model at the receiver. We evaluate RTP-Miner on a realworld RTP traffic dataset. The results show that RTP-Miner detects fuzzing in RTP header with more than 98% accuracy and less than 0.1% false alarm rate even when only 3% fuzzing is introduced. For the same fuzzing rate, it detects payload fuzzing -- a significantly more challenging problem -- with more than 80% accuracy and less than 2% false alarm rate. RTP-Miner has low memory and processing overheads that makes it well suited for deployment in real world VoIP infrastructure. |
| Starting Page | 87 |
| Ending Page | 92 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450300438 |
| DOI | 10.1145/1806565.1806587 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-06-02 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Fuzzing attacks Real-time transport protocol Machine learning Voip Denial of service Stochastic models |
| Content Type | Text |
| Resource Type | Article |
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