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

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

doi:10.1109/ISIT.2016.7541744

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

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

Department of Electrical Engineering & Computer Science

Research output: Chapter in Book/Entry/Poem › Conference contribution

2 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 language	English (US)
Title of host publication	Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2474-2478
Number of pages	5
Volume	2016-August
ISBN (Electronic)	9781509018062
DOIs	https://doi.org/10.1109/ISIT.2016.7541744
State	Published - Aug 10 2016
Event	2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain Duration: Jul 10 2016 → Jul 15 2016

Other

Other	2016 IEEE International Symposium on Information Theory, ISIT 2016
Country/Territory	Spain
City	Barcelona
Period	7/10/16 → 7/15/16

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

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10.1109/ISIT.2016.7541744

Cite this

Optimal Byzantine attack for distributed inference with M-ary quantized data. / Chen, Po Ning; Han, Yunghsiang S.; Lin, Hsuan Yin et al.
Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Vol. 2016-August Institute of Electrical and Electronics Engineers Inc., 2016. p. 2474-2478 7541744.

Research output: Chapter in Book/Entry/Poem › Conference contribution

Chen, PN, Han, YS, Lin, HY & Varshney, PK 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, 7541744, Institute of Electrical and Electronics Engineers Inc., pp. 2474-2478, 2016 IEEE International Symposium on Information Theory, ISIT 2016, Barcelona, Spain, 7/10/16. https://doi.org/10.1109/ISIT.2016.7541744

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AB - 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.

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

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