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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Joint BP and RNN for Resilient GPS Timing Against Spoofing Attacks

verfasst von : Sriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, Jinyun Zhang

Erschienen in: Artificial Intelligence for Communications and Networks

Verlag: Springer International Publishing

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Abstract

In this paper, we propose a new wide-area algorithm to secure the Global Positioning System (GPS) timing from spoofing attack. To achieve a trusted GPS timing, belief propagation (BP), recognized as one of the Artificial Intelligence (AI) approaches, and the recurrent neural network (RNN) are jointly integrated. BP is employed to authenticate each GPS receiving system in the wide-area network from malicious spoofing attacks and estimate the corresponding spoofing-induced timing error. To evaluate the spoofing status at each of the GPS receiving system, RNN is utilized to evaluate similarity in spoofing-induced errors across the antennas within the GPS receiving system. Having applied a proper training stage, simulation results show that the proposed joint BP-RNN algorithms can quickly detect the spoofed receiving system comparing with existing work.

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Metadaten
Titel
Joint BP and RNN for Resilient GPS Timing Against Spoofing Attacks
verfasst von
Sriramya Bhamidipati
Kyeong Jin Kim
Hongbo Sun
Philip Orlik
Jinyun Zhang
Copyright-Jahr
2019
Buch
Artificial Intelligence for Communications and Networks

Print ISBN: 978-3-030-22970-2

Electronic ISBN: 978-3-030-22971-9

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-22971-9_17

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