DISTRO: A System for Detecting Global Outliers from Distributed Data Streams with Privacy Protection

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 d...

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Bibliographic Details
Published inDatabase Systems for Advanced Applications pp. 477 - 481
Main Authors Zhang, Ji, Dekeyser, Stijn, Wang, Hua, Shu, Yanfeng
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Aggregation Cycle
Data Stream
Global Summary
Local Outlier
Outlier Detection
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Summary: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.
Bibliography:This work is partly supported by the Tasmanian ICT Centre, which is jointly funded by the Australian Government through the Intelligent Island Program and CSIRO.
ISBN:9783642120978
3642120970
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-12098-5_54