DISTRO: a system for detecting global outliers from distributed data streams with privacy protection

Authors:
Ji Zhang;Stijn Dekeyser;Hua Wang;Yanfeng Shu
Affiliations:
Department of Mathematics and Computing, The University of Southern Queensland, Australia;Department of Mathematics and Computing, The University of Southern Queensland, Australia;Department of Mathematics and Computing, The University of Southern Queensland, Australia;CSIRO ICT Centre, Hobart, Australia
Venue:
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Year:
2010

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Abstract

In this demo proposal, we present a new system, called DISTRO (a.k.a DIstributed STReam Outlier Detector), for detecting outliers from distributed data streams. DISTRO is able to effectively identify outliers from distributed data streams that are consistent with those generated by the centralized detection paradigm. DISTRO is also able to ensure high-level data privacy throughout the detection process. A number of optimization strategies are devised to further enhance its speed and communication performance. This proposal provides details on the motivation and technical challenges of detecting outliers from distributed data streams, presents an overview of DISTRO, and gives the plans for its system demonstration.