The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2024.0151145
PDF

Detecting GPS Spoofing Attacks Using Corrected Low-Cost INS Data with an LSTM Network

Author 1: Mohammed AFTATAH
Author 2: Khalid ZEBBARA

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 11, 2024.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: With the emergence of new technologies ranging from smart cities to the Internet of Things (IoT), many objects rely on satellite-based navigation systems, such as GPS, to accomplish their tasks securely. However, GPS receivers are exposed to various unintentional and intentional attacks, threatening the availability and reliability of the delivered information. GPS spoofing is considered as one of the most dangerous attacks, where attackers transmit intense signals on the same frequency to disrupt the GPS receiver, leading to erroneous position calculations. Detection methods for GPS spoofing are crucial to ensure secure navigation. This paper proposes a method for GPS spoofing detection that utilizes artificial intelligence algorithms in combination with raw data from an inertial navigation system (INS). Since INS sensors are prone to accumulating errors over time, these inaccuracies are corrected via a Long Short-Term Memory (LSTM) algorithm. The corrected accelerations and angular rates are then compared to the accelerations and angular rates estimated from the GPS data to detect GPS spoofing signals. This comparison uses the modified M-of-N method, demonstrating its effectiveness by a detection rate reaching 80% of the spoofing zones.

Keywords: Secure navigation; GPS spoofing; inertial systems; LSTM; M-of-N method; anti-spoofing techniques

Mohammed AFTATAH and Khalid ZEBBARA, “Detecting GPS Spoofing Attacks Using Corrected Low-Cost INS Data with an LSTM Network” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151145

@article{AFTATAH2024,
title = {Detecting GPS Spoofing Attacks Using Corrected Low-Cost INS Data with an LSTM Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151145},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151145},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Mohammed AFTATAH and Khalid ZEBBARA}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org