Detection of Spoofing Used Against the GNSS-Like Underwater Navigation Systems

As the demand for precision positioning grows around the world and spreads across various industries, initiatives are being taken to increasingly protect Global Navigation Satellite System (GNSS) receivers from intruders of all kinds, from unintentional industrial interference to advanced GNSS spoofing systems. The timing and cost of these forthcoming satellite navigation safety efforts are difficult to decipher due to the large number of new signals and constellations being deployed. However, it is safe to say that the newly designed anti-jamming and anti-spoofing GNSS systems open up new opportunities for innovative technologies. The false acoustic signal delay is equal to the sum of the spoofer receiving antenna delay, processing delay, and propagation delay from the spoofer to the victim. The victim finds the same location as the spoofer’s receiving antenna, and receivers located in different locations will have the same XYZ. The article presents classifications of terrorist attacks of this type.

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“…It is important to emphasize that the conversion of GNSS to LNSS is currently in the early stages of development [27][28][29][30][31].…”

Section: Discussionmentioning

confidence: 99%

GNSS and LNSS Positioning of Unmanned Transport Systems: The Brief Classification of Terrorist Attacks on USVs and UUVs

et al. 2021

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“…The highest levels of protection of location data are mandatory for the successful operation of a fleet of autonomous vessels. Therefore, a significant body of research on GNSS spoofing attack detection has been undertaken [134,[136][137][138].…”

Section: Ais Attackmentioning

confidence: 99%

Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

et al. 2022

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The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given particular consideration since it is a critical subcategory of many maritime infrastructures and, consequently, a target for cyber attacks. Recent research confirms that the dramatic proliferation of cyber crimes is fueled by increased levels of integration of new enabling technologies, such as IoT and Big Data. The trend to greater systems integration is, however, compelling, yielding significant business value by facilitating the operation of autonomous vessels, greater exploitation of smart ports, a reduction in the level of manpower and a marked improvement in fuel consumption and efficiency of services. Finally, practical challenges and future research trends have been highlighted.

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Detection and Mitigation of GNSS Spoofing Attacks in Maritime Environments Using a Genetic Algorithm

Singh

Sehra

et al. 2022

Mathematics

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Due to the high reliance of daily activities on the Global Navigation Satellite System (GNSS), its security is one of the major concerns for research and industry. Most navigation and mobile-driven location-based services use GNSS to render services. Due to the low power and easy access of GNSS signals, these signals are vulnerable to spoofing and other types of attacks. Recently many GNSS spoofing attacks have been identified in road- and maritime-based environments. This study provides a technique to detect and counter the GNSS spoofing attack in the maritime environment. This technique uses the Receiver Autonomous Integrity Monitoring (RAIM) model with Least Square Estimation (LSE) and Proportional Integral Derivative (PID) Control to detect the spoofing attack. The proposed technique is based on the concept of a genetic algorithm and navigation devices, such as inertial sensors and pilot options for the ship. A case study using the AIS dataset and simulation using MATLAB and NS3 is provided to validate the performance of the proposed approach. Nine different voyages from the AIS dataset were considered to check the accuracy and performance of the proposed algorithm. The accuracy of the proposed technique was analyzed using the correctly identified attack. The result shows that the proposed technique identifies spoofing attacks with an average value of 90 percent. For result analysis the considered nine routes were traversed multiple times. Root mean square error is used to calculate the positional mismatch (error rate). Based on the combined results analysis, the average value of RMSE is 0.28. In a best-case scenario, the proposed approach provides an RMSE value of 0.009.

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Detection of Spoofing Used Against the GNSS-Like Underwater Navigation Systems

Cited by 3 publications

References 4 publications

GNSS and LNSS Positioning of Unmanned Transport Systems: The Brief Classification of Terrorist Attacks on USVs and UUVs

GNSS and LNSS Positioning of Unmanned Transport Systems: The Brief Classification of Terrorist Attacks on USVs and UUVs

Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

Detection and Mitigation of GNSS Spoofing Attacks in Maritime Environments Using a Genetic Algorithm

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