A DoS Resilient Flow-level Intrusion Detection Approach for High-speed Networks

Global-scale attacks like viruses and worms are increasing in frequency, severity and sophistication, making it critical to detect outbursts at routers/gateways instead of end hosts. In this paper we leverage data streaming techniques such as the reversible sketch to obtain HiFIND, a High-speed Flow-level Intrusion Detection system. In contrast to existing intrusion detection systems, HiFIND 1) is scalable to flow-level detection on high-speed networks; 2) is DoS resilient; 3) can distinguish SYN flooding and various port scans (mostly for worm propagation) for effective mitigation; 4) enables aggregate detection over multiple routers/gateways; and 5) separates anomalies to limit false positives in detection. Both theoretical analysis and evaluation with several router traces show that HiFIND achieves these properties. To the best of our knowledge, HiFIND is the first online DoS resilient flow-level intrusion detection system for high-speed networks (approximately 10s of Gigabit/...

• Type: Conference
• Year: 2006
• Where: ICDCS
• Authors: Yan Gao, Zhichun Li, Yan Chen
• Keywords: Distributed And Parallel Computing, Flow-level Intrusion Detection, ICDCS 2006, Intrusion Detection System, flow-level Intrusion Detection