Pegasus: Precision hunting for icebergs and anomalies in network flows
Accurate online network monitoring is crucial for detecting attacks, faults, and anomalies, and determining traffic properties across the network. With high bandwidth links and consequently increasing traffic volumes, it is difficult to collect and analyze detailed flow records in an online manner. Traditional solutions that decouple data collection from analysis resort to sampling and sketching to handle large monitoring traffic volumes. We propose a new system, Pegasus, to leverage commercially available co-located compute and storage devices near routers and switches. Pegasus adaptively manages data transfers between monitors and aggregators based on traffic patterns and user queries. We use Pegasus to detect global icebergs or global heavy-hitters. Icebergs are flows with a common property that contribute a significant fraction of network traffic. For example, DDoS attack detection is an iceberg detection problem with a common destination IP. Other applications include identification of “top talkers,” top destinations, and detection of worms and port scans. Experiments with Abilene traces, sFlow traces from an enterprise network, and deployment of Pegasus as a live monitoring service on PlanetLab show that our system is accurate and scales well with increasing traffic and number of monitors.
computer network performance evaluation, computer network security, supervisory programs, system monitoring
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