@inproceedings{47adb81d670f40a0878943e7ed3a712a,
title = "Optimal Byzantine attack for distributed inference with M-ary quantized data",
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.",
author = "Chen, {Po Ning} and Han, {Yunghsiang S.} and Lin, {Hsuan Yin} and Varshney, {Pramod K.}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Symposium on Information Theory, ISIT 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = aug,
day = "10",
doi = "10.1109/ISIT.2016.7541744",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2474--2478",
booktitle = "Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory",
}