Joint Sequential Detection and Isolation of Anomalies under Composite Hypotheses

Anamitra Chaudhuri, Georgios Fellouris

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

Abstract

A setup with multiple, independent, sequentially monitored data streams is considered. For each of them, two composite hypotheses are postulated, with the interpretation that the stream is anomalous if the corresponding alternative hypothesis holds. It is of interest to detect as quickly as possible whether there is at least one anomalous stream, and also to identify upon stopping the subset of anomalous streams. To address this joint sequential detection and isolation problem, we propose a sequential multiple testing framework where the probabilities of four kinds of error are controlled below distinct, user-specified levels. Two of them refer to the detection task, and the other two to the isolation task. A testing policy is proposed and it is shown to achieve the minimum possible expected sample size, under each point of the parameter space, to a first order asymptotic approximation as the four target error probabilities go to 0. The general theory is illustrated in the case that the data streams generate iid observations that belong to a multiparameter exponential family.

Original languageEnglish (US)
Title of host publication2024 IEEE International Symposium on Information Theory, ISIT 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1486-1491
Number of pages6
ISBN (Electronic)9798350382846
DOIs
StatePublished - 2024
Externally publishedYes
Event2024 IEEE International Symposium on Information Theory, ISIT 2024 - Athens, Greece
Duration: Jul 7 2024Jul 12 2024

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference2024 IEEE International Symposium on Information Theory, ISIT 2024
Country/TerritoryGreece
CityAthens
Period7/7/247/12/24

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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