Optimal Byzantine attack for distributed inference with M-ary quantized data

Po Ning Chen, Yunghsiang S. Han, Hsuan Yin Lin, Pramod Kumar Varshney

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

1 Scopus citations

Abstract

In many applications that employ wireless sensor networks (WSNs), robustness of distributed inference against Byzantine attacks is important. In this work, distributed inference is considered when local sensors send M-ary data to the fusion center. The optimal Byzantine attack policy is then derived under the assumption that the Byzantine adversary has the knowledge of the statistics of local quantization outputs. Our analysis indicates that the fusion center can be blinded such that the detection error is as poor as a random guess when an adequate fraction of sensors are compromised.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2474-2478
Number of pages5
Volume2016-August
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
CountrySpain
CityBarcelona
Period7/10/167/15/16

ASJC Scopus subject areas

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

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    Chen, P. N., Han, Y. S., Lin, H. Y., & Varshney, P. K. (2016). Optimal Byzantine attack for distributed inference with M-ary quantized data. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory (Vol. 2016-August, pp. 2474-2478). [7541744] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541744