Detecting Anomalies in Graphs with Numeric Labels
Data(s) |
01/10/2011
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Resumo |
This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-related examples and validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, Yagada detects twice as many anomalies as the best-performing numeric discretization algorithm. Qualitative evaluation shows that the detected anomalies are meaningful, representing a com- bination of structural irregularities and numerical outliers. |
Identificador | |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/restrictedAccess |
Fonte |
Davis , M , Liu , W , Miller , P & Redpath , G 2011 , ' Detecting Anomalies in Graphs with Numeric Labels ' Paper presented at 20th ACM Conference on Information and Knowledge Management , Glasgow , United Kingdom , 24/10/2011 - 28/10/2011 , pp. 1197-1202 . DOI: 10.1145/2063576.2063749 |
Tipo |
conferenceObject |