An outlier ensemble for unsupervised anomaly detection in honeypots data
Author:
Affiliation:
1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
2. CEDRIC lab, Conservatoire National des Arts et Métiers, Paris, France
Publisher
IOS Press
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science
Reference25 articles.
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3. A. Lazarevic and V. Kumar, Feature bagging for outlier detection, in: KDD ’05 Proc. of the Eleventh ACM SIGKDD Int. Conf. on Knowledge Discovery in Data Mining, 2005, pp. 157–166.
4. Ensembles for unsupervised outlier detection: challenges and research questions a position paper;Zimek;ACM SIGKDD Explorations Newsletter,2013
5. Outlier ensembles: position paper;Aggarwal;ACM SIGKDD Explorations Newsletter,2012
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