Graph based anomaly detection and description: A survey

Data Mining and Knowledge Discovery

Volumn 29, Issue 3, 2015, Pages 626-688

  Akoglu, Leman ^a   Tong, Hanghang ^b   Koutra, Danai ^c  

^a Stony Brook University   (United States)

^b City College of New York   (United States)

^c Computer Science Department Carnegie Mellon University ^*  (United States)

Author keywords

Anomaly description; Anomaly detection; Change point detection; Event detection; Fraud detection; Graph mining; Network anomaly detection; Visual analytics

Indexed keywords

LAWS AND LEGISLATION; SURVEYS;

ANOMALY DESCRIPTION; ANOMALY DETECTION; CHANGE POINT DETECTION; EVENT DETECTION; FRAUD DETECTION; GRAPH MINING; NETWORK ANOMALY DETECTION; VISUAL ANALYTICS;

GRAPHIC METHODS;

EID: 84940282157     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-014-0365-y     Document Type: Article

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