ROBUST ANOMALY DETECTION AND REGULARIZED DOMAIN AD

专利名称：ROBUST ANOMALY DETECTION AND

REGULARIZED DOMAIN ADAPTATION OFCLASSIFIERS WITH APPLICATION TOINTERNET PACKET-FLOWS

发明人：David J. Miller,George Kesidis,Jayaram

Raghuram

申请号：US13465741申请日：20120507

公开号：US20120284791A1公开日：20121108

摘要：Sound, robust methods identify the most suitable, parsimonious set of tests touse with respect to prioritized, sequential anomaly detection in a collected batch ofsample data. While the focus is on detecting anomalies in network traffic flows andclassifying network traffic flows into application types, the methods are also applicableto other anomaly detection and classification application settings, including detectingemail spam, (e.g. credit card) fraud detection, detecting imposters, unusual eventdetection (for example, in images and video), host-based computer intrusion detection,detection of equipment or complex system failures, as well as of anomalousmeasurements in scientific experiments.

申请人：David J. Miller,George Kesidis,Jayaram Raghuram

地址：State College PA US,State College PA US,State College PA US

国籍：US,US,US

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