An evaluation of automatic parameter tuning of a statistics-based anomaly detection algorithm

International Journal of Network Management

Volumn 20, Issue 5, 2010, Pages 295-316

  Himura, Yosuke ^a   Fukuda, Kensuke ^b   Cho, Kenjiro ^c   Esaki, Hiroshi ^a  

^a UNIVERSITY OF TOKYO   (Japan)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

^c Internet Initiative Japan Inc   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ANOMALY DETECTION METHODS; ANOMALY-DETECTION ALGORITHMS; AUTOMATIC TUNING; DETECTION PERFORMANCE; DYNAMIC PARAMETERS; DYNAMIC TUNING; FIXED PARAMETERS; GAMMA MODELS; JAPAN STANDARD TIME; MULTISCALES; NETWORK TRAFFIC; PARAMETER LEARNING; PARAMETER PREDICTION; PARAMETER SETTING; PARAMETER-TUNING; PERIODIC CORRELATION; REAL TRAFFIC; REAL-TIME DETECTION; UNSUPERVISED METHOD;

NORMAL DISTRIBUTION; RANDOM PROCESSES; SIGNAL DETECTION; TUNING;

PARAMETER ESTIMATION;

EID: 77956385147     PISSN: 10557148     EISSN: 10991190     Source Type: Journal    
DOI: 10.1002/nem.749     Document Type: Article

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