Detection of Untrustworthy IoT Measurements Using Expert Knowledge of Their Joint Distribution

Ilia Nouretdinov, Salaheddin Darwish, Stephen Wolthusen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

The aim of this work is to discuss abnormality detection and explanation challenges motivated by Medical Internet of Things. First, any feature is a measurement taken by a sensor at a time moment, so abnormality detection also becomes a sequential process. Second, an anomaly detection process could not rely on having a large collection of data records, but instead there is a knowledge provided by the experts.
Original languageEnglish
Title of host publication16th International Conference On Smart homes and health Telematics (ICOST'2018)
PublisherSpringer
Pages310-316
Number of pages7
ISBN (Electronic)978-3-319-94523-1
ISBN (Print)978-3-319-94522-4
DOIs
Publication statusPublished - 2018
Event16th International Conference On Smart homes and health Telematics: ICOST - Singapore
Duration: 10 Jul 201812 Jul 2018
http://www.icostconference.org/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10898

Conference

Conference16th International Conference On Smart homes and health Telematics
Period10/07/1812/07/18
Internet address

Keywords

  • anomaly explanation
  • untrustworthy data
  • Internet of Things

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