Sequential anomaly detection with observation control under a generalized error metric

Aristomenis Tsopelakos, Georgios Fellouris

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

Abstract

The problem of sequential anomaly detection is considered under sampling constraints and generalized error control. It is assumed that there is no prior information on the number of anomalies. It is required to control the probability at least k errors, of any kind, upon stopping, where k is a user specified integer. It is possible to sample only a fixed number of processes at each sampling instance. The processes to be sampled are determined based on the already acquired observations. The goal is to find a procedure that consists of a stopping rule and a decision rule and a sampling rule that satisfy the sampling and error constraints, and have as small as possible average sample size for every possible scenario regarding the subset of anomalous processes. We characterize the optimal expected sample size for this problem to a first order approximation as the error probability vanishes to zero, and we propose procedures that achieve it. The performance of those procedures is compared in a simulation study for different values of k.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1165-1170
Number of pages6
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: Jul 21 2020Jul 26 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
CountryUnited States
CityLos Angeles
Period7/21/207/26/20

Keywords

  • Anomaly detection
  • asymptotic optimality
  • generalized error
  • sampling design

ASJC Scopus subject areas

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

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