FRaC: A feature-modeling approach for semi-supervised and unsupervised anomaly detection

Data Mining and Knowledge Discovery

Volumn 25, Issue 1, 2012, Pages 109-133

  Noto, Keith ^a   Brodley, Carla ^a   Slonim, Donna ^a  

^a Tufts University   (United States)

Author keywords

Anomaly detection; Unsupervised learning

Indexed keywords

ANOMALY DETECTION; ANOMALY DETECTION METHODS; FEATURE MODELS; MACHINE-LEARNING; ONE-CLASS SUPPORT VECTOR MACHINE; SEMI-SUPERVISED; TRAINING DATA; TRAINING SETS; UNSUPERVISED ANOMALY DETECTION;

COMPUTER CRIME; INTRUSION DETECTION; UNSUPERVISED LEARNING;

CRIME;

EID: 84859537598     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-011-0234-x     Document Type: Article

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