Attack Detection and Defense System Using an Unknown Input Observer for Cooperative Adaptive Cruise Control Systems

Yamamoto, Yudai; Kuze, Naomi; Ushio, Toshimitsu

doi:10.1109/access.2021.3124547

Cited by 11 publications

(8 citation statements)

References 41 publications

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“…As shown in Figure 3a, one can find the detection time (t = 58.7 s) under the adaptive threshold is smaller than that (t = 65.9 s) under the precomputed threshold. In contrast to the work in [28], one can find that the developed detection method can reduce attack detection time. In addition, the detection rate analysis method under a certain attack intensity is used to evaluate the performance of the proposed detection method in [29].…”

Section: Performance Of the Proposed Detection Methodsmentioning

confidence: 78%

“…Case 1 is to show the detection performance of the proposed detection method by comparing the work in [28,29]. Case 2 is to demonstrate the effectiveness of the developed detection and isolation method.…”

Section: Resultsmentioning

confidence: 99%

“…Figure3. The detection analysis of FDI attacks under the adaptive threshold and precomputed threshold in[28]: (a) Detection time of FDI attack under the adaptive threshold and precomputed threshold in[28]; (b) Detection rate of FDI attack under the adaptive threshold and precomputed threshold in[28].…”

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confidence: 99%

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Detection and Isolation of False Data Injection Attack in Intelligent Transportation System via Robust State Observer

Huang

Wang

2022

Processes

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As the future of transportation systems, the intelligent transportation system is a promising technology to improve the increasingly serious traffic problems. However, the integration of cyber-physical systems makes them vulnerable to new cyber–physical attacks. To ensure the security of intelligent transportation systems, a novel robust state observer-based detection and isolation method against false data injection attacks is developed. Based on the constructed dynamic model of intelligent vehicle networking, the covert characteristic of a false data injection attack is analyzed. Then, a novel state residuals-based detection criterion is developed by using a real-time observed state. To shorten the detection time, an adaptive detection threshold is designed to replace the existing computed threshold. In addition, robust state observer banks are established to isolate multiple injected attacks. Finally, simulation results on the vehicle networking system demonstrate the effectiveness of the developed detection and isolation method against false data injection attacks.

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Section: Performance Of the Proposed Detection Methodsmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 99%

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Detection and Isolation of False Data Injection Attack in Intelligent Transportation System via Robust State Observer

Huang

Wang

2022

Processes

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“…It is obvious that the error of state estimation under adaptive unknown input observers is smaller than that under robust state observers. Compared with the UIO-based detection work in Huang and Wang 33 and Yamamoto et al, 34 the performance of state estimation error can be shortened. Furthermore, the false positive rate under the precomputed threshold is used to evaluate the detection performance against FDIA, as shown in Figure 6(b).…”

Section: Guidelines For Manuscript Preparationmentioning

confidence: 99%

“…However, the above learning-based detection methods relay on the training of historical data. Thus, a physical dynamic model-based detection methods against FDIAs were proposed in Huang and Wang 33 and Yamamoto et al 34 In Huang and Wang, 33 a robust state observer-based detection method against FDIAs was proposed. Yamamoto et al 34 developed an UIO-based detection method against FDIAs in vehicle networking system based on a state residuals.…”

Section: Introductionmentioning

confidence: 99%

Adaptive unknown input observer-based detection and identification method for intelligent transportation under malicious attack

Cheng

Pan

Zhang

2023

Measurement and Control

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This paper aims at developing a novel detection and identification method against malicious attacks in intelligent transportation. Due to the development and applications of communication and advanced sensor technologies, intelligent transportation has faced new safety risks. In particular, the emerging malicious attacks, such as false data injection attack, can mask the destruction of physical dynamic by tampering with information in layer to fool the current detection methods. Because of this reason, an adaptive unknown input observer-based detection and identification method is developed. Firstly, a physical dynamics model of vehicle networking system is established by considering the actual physical state. Considering the spoofing characteristics of false data injection attack, an unknown input observer-based detection method is proposed. Through the design of adaptive unknown input observer parameters, the detection performance, can be improved by cutting down the state estimation error. Compared with the UIO-based detection method, simulations demonstrate that the false positive rate can be reduced 0.1%. Based on the feature of state residuals that is not sensitive to the attacked ith residual, but sensitive to other residuals, a novel identification criterion is developed. At last, simulation experiments on the Matlab verify the performance of the proposed detection and identification algorithm in intelligent transportation system.

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A Comprehensive Review on Cyber-Attack Detection and Control of Microgrid Systems

Shafei

Aguilera

2023

Power Systems

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Attack Detection and Defense System Using an Unknown Input Observer for Cooperative Adaptive Cruise Control Systems

Cited by 11 publications

References 41 publications

Detection and Isolation of False Data Injection Attack in Intelligent Transportation System via Robust State Observer

Detection and Isolation of False Data Injection Attack in Intelligent Transportation System via Robust State Observer

Adaptive unknown input observer-based detection and identification method for intelligent transportation under malicious attack

A Comprehensive Review on Cyber-Attack Detection and Control of Microgrid Systems

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