Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach
Author:
Affiliation:
1. Carnegie Mellon University, Pittsburgh, PA, USA
2. National University of Singapore, Singapore, Singapore
3. KAIST, Daejeon, South Korea
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3292500.3330946
Reference29 articles.
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3. oddball: Spotting Anomalies in Weighted Graphs
4. Graph based anomaly detection and description: a survey
5. Alex Beutel Wanhong Xu Venkatesan Guruswami Christopher Palow and Christos Faloutsos. 2013. Copycatch: stopping group attacks by spotting lockstep behavior in social networks. In WWW . 10.1145/2488388.2488400 Alex Beutel Wanhong Xu Venkatesan Guruswami Christopher Palow and Christos Faloutsos. 2013. Copycatch: stopping group attacks by spotting lockstep behavior in social networks. In WWW . 10.1145/2488388.2488400
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