Honeypots: Tracking Hackers
Aguri: An Aggregation-Based Traffic Profiler
COST 263 Proceedings of the Second International Workshop on Quality of Future Internet Services
K-T.R.A.C.E: A kernel k-means procedure for classification
Computers and Operations Research
Visual Analytics for Network Flow Analysis
CATCH '09 Proceedings of the 2009 Cybersecurity Applications & Technology Conference for Homeland Security
Portscan Detection with Sampled NetFlow
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
Proceedings of the Symposium on Computer Human Interaction for the Management of Information Technology
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This paper presents a network monitoring framework with an intuitive visualization engine. The framework leverages a kernel method with spatial and temporal aggregated IP flows for the off/online processing of Netflow records and full packet captures from ISP and honeypot input data and is operating on aggregated Netflow records and is supporting network management activities related to the anomaly and attack detection.