Casting out Demons: Sanitizing Training Data for Anomaly Sensors

The efficacy of anomaly detection (AD) sensors depends heavily on the quality of the data used to train them. Artificial or contrived training data may not provide a realistic view of the deployment environment. Most realistic data sets are dirty; that is, they contain a number of attacks or anomalo...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Cretu, G.F., Stavrou, A., Locasto, M.E., Stolfo, S.J., Keromytis, A.D.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Application software Casting Computer science Computer security Data privacy Data security Intrusion detection Telecommunication traffic Traffic control Training data
Online-Zugang:	Volltext bestellen
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