A Jamming Aware Artificial Potential Field Method to Counter GPS Jamming for Unmanned Surface Ship Path Planning

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

doi:10.1109/jsyst.2023.3237613

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…The authors present a jamming attack in [7] by blocking the communication channel between PLC and other components such as PLCs, actuators, and SCAD systems in SWaT. Jamming attacks prevent sending the information [9], [10], which negatively impacts the performance of SWaT and damages some water components.…”

Section: Introductionmentioning

confidence: 99%

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

Addeen,

Xiao,

2024

IEEE Access

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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.

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Section: Introductionmentioning

confidence: 99%

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

Addeen,

Xiao,

2024

IEEE Access

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“…First, the DAT algorithm is designed in the controller, which can control the time the USVs formation reach stability. Then, each USV is equipped with distance and direction sensors to measure the relative positions of neighbours [28], [29], and the formation of USVs is controlled with different scale factors to improve the stability and robustness of its formation control. Finally, the effectiveness of the proposed control scheme is verified by simulation.…”

mentioning

confidence: 99%

DAT-Based Formation Control With Different Scale Factor of Relative Information Measurement

Fu,

Wang,

Huang

et al. 2024

IEEE Access

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This paper proposes an unmanned surface vehicles (USVs) formation control method based on distributed average tracking (DAT) with different relative information measurement scale factors. Firstly, the DAT algorithm is designed in the controller to control the time when the system reaches stability. Then, the relative position information of adjacent USVs is measured by installing distance sensors and direction sensors on each USV, and different scale factors are used to control the formation of USVs, and improve the stability and robustness of its control system. Finally, the effectiveness of the method proposed in this paper is verified by numerical simulation experiments. INDEX TERMS DAT, different scale factor, information measurement I. INTRODUCTION

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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework

Chen,

Liu,

Zhao

et al. 2024

Ocean & Coastal Management

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A Jamming Aware Artificial Potential Field Method to Counter GPS Jamming for Unmanned Surface Ship Path Planning

Cited by 9 publications

References 30 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

DAT-Based Formation Control With Different Scale Factor of Relative Information Measurement

Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework

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