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TDOA Source-Localization Technique Robust to Time-Synchronization Attacks

delete2021-01-01
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M
Marguerite Delcourt *
J
Jean‐Yves Le Boudec
DOI:10.1109/TIFS.2020.3001741delete
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摘要

摘要

En 中文
In this paper, we focus on the localization of a passive source from time difference of arrival (TDOA) measurements. TDOA values are computed with respect to pairs of fixed sensors that are required to be accurately time-synchronized. This constitutes a weakness as all synchronization techniques are vulnerable to delay injections. Attackers are able either to spoof the signal or to inject asymmetric delays in the communication channel. By nature, TDOA measurements are highly sensitive to time-synchronization offsets between sensors. We first illustrate that time-synchronization attacks can severely affect the localization process. With a delay of a few microseconds injected on one sensor, the resulting estimate might be several kilometers away from the true location of the unknown source. We show that residual analysis does not enable the detection and identification of time-synchronization attacks. Our main contribution is then to propose a two-step TDOA-localization technique that is robust against time-synchronization attacks. It uses a known source to define a weight for each pair of sensors, reflecting the confidence in their time synchronization. Our solution then uses the weighted least-squares estimator with the newly created weights and the TDOA measurements received from the unknown source. As a result, our method either identifies the network as being too corrupt to localize, or gives a corrected estimate of the unknown position along with a confidence metric. Numerical results illustrate the performance of our technique.
Keyword:
Sensors
Delays
Synchronization
Calibration
Frequency estimation
Oscillators
Communication system security
electronic warfare
source localization
TDOA
time-synchronization attack
wireless sensor networks
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期刊

IEEE Transactions on Information Forensics and Security 封面图
IEEE Transactions on Information Forensics and Security
IF:
8
论文数:
5.3K
被引数:
2.3W

机构

S
swiss federal institutes of technology domain
学者数:
9.0W
论文数: 8.0W
被引数: 163
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