Quickest Detection of a Dynamic Anomaly in a Sensor Network

Georgios Rovatsos, George V. Moustakides, Venugopal V. Veeravalli

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

Abstract

We study the problem of detecting the emergence of a dynamic anomaly in sensor networks. The generated observations initially follow a pre-change distribution. At some unknown time, an anomaly appears, affecting a different set of nodes at each instant. The affected nodes generate data according to a post-change distribution. It is assumed that the trajectory of the anomaly is unknown. We propose a test that is optimal with respect to a measure of the expected delay for the worst-case trajectory. We compare the optimal test numerically with a test that uses the knowledge of the path of the anomaly and a heuristic test.

Original languageEnglish (US)
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages98-102
Number of pages5
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: Nov 3 2019Nov 6 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
CountryUnited States
CityPacific Grove
Period11/3/1911/6/19

Keywords

  • Sensor networks
  • dynamic anomaly
  • quickest change detection
  • worst-path approach

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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