Optimal Allocation of False Data Injection Attacks for Networked Control Systems With Two Communication Channels

Guo, Li; Yu, Hao; Hao, Fei

doi:10.1109/tcns.2020.3030002

Cited by 33 publications

(9 citation statements)

References 34 publications

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“…22 For this reason, the spoofing characteristics of FDIAs can fool the above security detection mechanisms. In Guo et al, 23 Guo et al analyzed the spoofing feature of FDIAs, and given the optimal attack strategy. In Kwon et al, 24 three kinds of stealthy FDIAs were studied based on the ability of attackers.…”

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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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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“…In Manandhar et al (2014), the problem of fault and false data injection attack detection in smart grids is investigated using the Kalman filter. The problem of attack allocation with resource constraints is studied in Guo et al (2020) where the communication channels are jammed with false data injection attacks.…”

Section: Introductionmentioning

confidence: 99%

Decentralized event-triggered resilient control for a class of networked control systems under denial-of-service attacks

Torabi

Zarei

Saif

2023

Transactions of the Institute of Measurement and Control

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This paper studies the problem of resilient dynamic output-feedback control schemes for continuous-time networked control systems (NCSs). A decentralized hybrid strategy is utilized while network imperfections, external disturbances, and noise are considered. Moreover, during data transmission, a practical denial-of-service (DoS) jamming attack, which periodically disturbs the network channels, is considered. To preserve the network resources, a decentralized event-triggered mechanism is employed to transmit only the sampled signals that are required. It is assumed that outputs and control inputs of each subsystem are transmitted to the corresponding decentralized controllers and actuators, respectively, over the different individual channels based on independent triggering mechanisms. At first, the NCS is modeled as a decentralized hybrid system with exogenous disturbance and noise. Then, sufficient conditions that guarantee the [Formula: see text]-stability of the NCS in the presence of external disturbances and noise, which is resilient to periodic DoS attacks, are provided in terms of the linear matrix inequalities. Finally, sufficient conditions are derived to deal with the time-varying delays. It has been demonstrated that the proposed technique can be effectively applied to a well-known continuous stirred tank reactor (CSTR) as a benchmark example.

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“…To sum up, lots of detection methods against Dos attacks were developed to ensure the safety of vehicle networking systems. Different from the above Dos attacks, the emerging false data injection (FDI) attacks are more deceptive [15][16][17]. By tampering with the transmitted data, the FDI attacks can spoof the common detection method.…”

Section: Introductionmentioning

confidence: 99%

“…To respond to the FDI attacks timely, scholars have carried out some research on the security of vehicle networking systems under FDI attacks [16][17][18][19][20]. In [16], L. Guo et al investigated the covert characteristics of FDI attacks and gave the optimal attack strategies with respect to the cyber-physical system of intelligent vehicle networking. In addition, the FDI attack was modeled as an additive attack that affects the vehicle platoon, and a new assessment method was developed [17].…”

Section: Introductionmentioning

confidence: 99%

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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Optimal Allocation of False Data Injection Attacks for Networked Control Systems With Two Communication Channels

Cited by 33 publications

References 34 publications

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

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

Decentralized event-triggered resilient control for a class of networked control systems under denial-of-service attacks

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

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