Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships

Wang, Jia; Xiao, Yang; Li, Tieshan; Chen, C. L. Philip

doi:10.3390/electronics11050801

Cited by 12 publications

(6 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, they have low computational powers and small memories, making it hard to secure them by applying heavy encryption security algorithms [18], [19]. Another example is the IoT devices communicate with each other based on different communication networks such as Wi-Fi, Near-Field Communication (NFC), and Global Positioning System (GPS) [20]. However, most of these networks are vulnerable to DoS attacks, which affect the availability of accessing data all the time [21], [22].…”

Section: B Wds Security Issuementioning

confidence: 99%

A CVAE-Based Anomaly Detection Algorithm for Cyber Physical Attacks for Water Distribution Systems

Addeen,

Xiao,

2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

Modern technologies adopt Internet of Things (IoT) devices to increase water management efficiency and enhance water quality services. However, the limitations of IoT devices, such as small sizes and poor security, weaken the Water Distribution System (WDS) security, and many attackers compromise the critical components of WDS. Cyber-physical attacks (CPAs) are considered one of the biggest challenges that decrease the security factors in WDS by disrupting normal operations and tampering with the critical data of the water system. For instance, an attacker can change the water pump's speed, disrupting the service. An attacker can also alter the data of water quality parameters to contaminate the water. It is important to propose solutions to increase security in the WDS and defend against CPAs and security threats. Although several intrusion detection methods were proposed in the literature to detect WDS CPAs, many issues still need solutions, such as detecting attacks with smaller false alarms, minimizing the time to disclose the attacks, determining the location of the compromising components, and recovering solutions for the attacked components. Therefore, this paper proposes a model based on a deep learning algorithm called a Conditional variational Autoencoder (CVAE) to disclose CPAs and mitigate their bad effects on WDS. The proposed method consists of a neural network, an encoder to compress data, and a decoder to decompress data. The objective goal is to minimize the reconstruction error between the encoded-decoded data and the initial data. We apply the CVAE on some well-known datasets. The experiment results show that our proposed CVAE method performs better than others. After analyzing the CVAE model with other existing models, we get the highest performance by reaching %98 accuracy.

show abstract

Section: B Wds Security Issuementioning

confidence: 99%

A CVAE-Based Anomaly Detection Algorithm for Cyber Physical Attacks for Water Distribution Systems

Addeen,

Xiao,

2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…These attacks encompass sophisticated techniques such as DoS, jamming, and spoofing, each posing distinct challenges to the security and reliability of MASS operations [36]. It is essential to delve into the technical details of these cyberattacks, aligning them with corresponding Tactics, Techniques, and Procedures (TTPs) specific to the MASS context [52].…”

Section: Cyberattacks In Mass Ecosystemmentioning

confidence: 99%

“…Implementing advanced intrusion detection systems and signal processing techniques proves essential in identifying anomalous patterns while developing resilient communication protocols and alternative frequency channels enhances the system's robustness against jamming attempts. DoS Attacks emerge as a critical cybersecurity concern, challenging the system's resilience [41] [52]. To assess its robustness, the study executed a DoS assault by overwhelming the AIS receivers with simultaneous signals generated using our enhanced AISTX in [41].…”

Section: B Jamming Attacksmentioning

confidence: 99%

Maritime Autonomous Surface Ships: A Review of Cybersecurity Challenges, Countermeasures, and Future Perspectives

Tabish,

Chaur-Luh

2024

IEEE Access

View full text Add to dashboard Cite

Maritime Autonomous Surface Ships (MASS) have brought a transformative wave in the marine industry, yielding unprecedented operational advancements and efficiency gains. However, this paradigm shift has concurrently raised substantial cybersecurity concerns that demand meticulous attention to mitigate the impact of attacks on MASS stability. This study presents a comprehensive examination of the cybersecurity landscape, shedding light on prevalent issues concerning the data independence, integrity, and connectivity of MASS. The effectiveness of existing defense strategies against both inbound and outbound cyberattacks, focusing on attack detection and classification, is rigorously scrutinized. This analysis encompasses regulatory frameworks, encryption methods, intrusion detection systems, and a systematic approach to identifying and categorizing cyber threats. Additionally, the study anticipates future developments in cyber threats and proposes innovative solutions to fortify MASS defenses against potential cybersecurity vulnerabilities. To align with cybersecurity standards, this paper integrates challenges, possible solutions, and future advancements in a structured and cohesive manner, ensuring a thorough understanding of the intricate cybersecurity ecosystem surrounding Maritime Autonomous Surface Ships.

show abstract

“…When there are multiple spoofing signals, this method may also fail, and forming a null for the spoofing signal will also cause a certain degree of attenuation of the real signal power [20,21]. Additionally, the cost of large-scale dedicated antenna arrays is high, limiting its practical applications [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Spoofing Detection Method Using Three Low-Cost Antennas in Satellite Navigation

Chen,

Wang,

Fang

et al. 2024

Electronics

View full text Add to dashboard Cite

The vulnerability of civil receivers of the Global Satellite Navigation System (GNSS) to spoofing jamming has raised significant concerns in recent times. Traditional multi-antenna spoofing detection methods are limited in application scenarios and come with high hardware costs. To address this issue, this paper proposes a novel GNSS spoofing detection method utilizing three low-cost collinear antennas. By leveraging the collinearity information of the antennas, this method effectively constrains the observation equation, leading to improved estimation accuracy of the pointing vector. Furthermore, by employing a binary statistical detection model based on the sum of squares (SSE) between the observed value and the estimated value of the pointing vector, real-time spoofing signal detection is enabled. Simulation results confirm the efficacy of the proposed statistical model, with the error of the skewness coefficient not exceeding 0.026. Experimental results further demonstrate that the collinear antenna-based method reduces the standard deviation of the angle deviation of the pointing vector by over 55.62% in the presence of spoofing signals. Moreover, the experiments indicate that with a 1 m baseline, this method achieves 100% spoofing detection.

show abstract

Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships

Cited by 12 publications

References 27 publications

A CVAE-Based Anomaly Detection Algorithm for Cyber Physical Attacks for Water Distribution Systems

A CVAE-Based Anomaly Detection Algorithm for Cyber Physical Attacks for Water Distribution Systems

Maritime Autonomous Surface Ships: A Review of Cybersecurity Challenges, Countermeasures, and Future Perspectives

A Real-Time Spoofing Detection Method Using Three Low-Cost Antennas in Satellite Navigation

Contact Info

Product

Resources

About