Detection of GNSS spoofing using the Fourier transform of correlator outputs and mitigation using an autoencoder neural network

Abstract

Present study focuses on defense against carry-off-type spoofing attacks which often cause distortion in the correlation function profile. Investigation of the frequency characteristics of the correlation function is proposed to detect the presence of the spoofing signal. Having detected the spoofing signal, it is suggested to use an autoencoder neural network to deal with the impacts of the spoofing. The autoencoder neural network removes distortions caused by the spoofing signal from the correlation function. Results demonstrate that the proposed detection method achieves a higher than 98% detection rate and autoencoder-based approach mitigates spoofing attacks by an average of 92.64%.

Keywords:

• GNSS
• Spoofing attack
• Detection
• Mitigation
• Receiver tracking loop
• Autoencoder neural network
• Fuzzy logic

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

S. Tohidi

S. Tohidi is Ph.D. student in the Department of Electrical Engineering. at Iran University of Science and Technology. Her research interests include signal processing, artificial intelligence, and GPS applications.

M. R. Mosavi

M. R. Mosavi (Corresponding Author) received his B.S., M.S., and Ph.D. degrees in Electronic Engineering from Iran University of Science and Technology (IUST), Tehran, Iran in 1997, 1998, and 2004, respectively. He is currently faculty member (full professor) of the Department of Electrical Engineering of IUST. He is the author of more than 500 scientific publications in journals and international conferences in addition to 12 academic books. His research interests include circuits and systems design. He is also editor-in-chief of Iranian Journal of Marine Technology and editorial board member of Iranian Journal of Electrical and Electronic Engineering and GPS Solutions.

A. A. Abedi

A. A. Abedi received his B.S. degree in Electronic Engineering from Esfahan University in 2004, Esfahan, Iran, M.S. degree in Electronic Engineering from Tarbiat Modares University in 2006, Tehran, Iran, and Ph.D. degree in Electronic Engineering from Iran University of Science and Technology (IUST), Tehran, Iran in 2019. His research interests include GNSS and applications.