False Data Injection Attacks in Bilateral Teleoperation Systems

Dong, Yimeng; Gupta, Nirupam; Chopra, Nikhil

doi:10.1109/tcst.2019.2903446

Cited by 27 publications

(13 citation statements)

References 23 publications

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“…where M 0 represents null hypothesis, M 1 represents under attack hypothesis, ρ represents threshold discussed in [100,101] used for the SCADA system, and the same results have been shown in [102]. Q 2 detector with cosine has been explained in [95,103,104] for the detection of false data injection attacks which affects smart grid. An algorithm is discussed for the detection of deception attack in an application which could be remote state application, smart sensors used for data receiving [105].…”

Section: Q 2 Detector Kalman Filtersmentioning

confidence: 86%

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An Overview of Recent Advances of Resilient Consensus for Multiagent Systems under Attacks

Aslam

Ahmed

et al. 2022

Computational Intelligence and Neuroscience

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Consensus control of multiagent systems (MASs) has been one of the most extensive research topics in the field of robotics and automation. The information sharing among the agents in the MASs depends upon the communication network because the interaction of agents may affect the consensus performance of the agents in a communication network. An unexpected fault and attack may occur on one agent and can propagate through the communication network into other agents. Thus, this may cause severe degradation of the whole MASs. In this paper, we first discussed MAS technologies. After that available technologies for the modeling of attacks and fundamental issues due to attacks on MAS attacks were discussed. We also introduced cooperative attack methodologies and model-based attack methodology. Objective of this article is to provide comprehensive study on recent advances in consensus control of MASs under attacks covering the published results until 2021. This survey presents different kinds of attacks, their estimation and detection, and resilient control against attacks. At the end, the survey accomplishes some potential recommendations for future direction to solve the key issues and challenges reported for secure consensus control of MASs.

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Section: Q 2 Detector Kalman Filtersmentioning

confidence: 86%

“…By applying suitable threshold, we can find malicious node. Some numerical results of such malicious nodes has been studied in [92,95]. With the use of this model, we can find malicious node.…”

Section: Simulation Environment For Agent-based Mas Networkmentioning

confidence: 99%

An Overview of Recent Advances of Resilient Consensus for Multiagent Systems under Attacks

Aslam

Ahmed

et al. 2022

Computational Intelligence and Neuroscience

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“…This attack is fully discussed with proof in [38]. The contribution in this work is done on attack detection using the DL techniques.…”

Section: Assumptionmentioning

confidence: 99%

Deep Learning-based Attack Detector for Bilateral Teleoperation Systems

Al-Wajih

Hamdan

Mohaya

et al. 2022

IJRCS

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A teleoperation system is referred to as a plant that is controlled remotely, and it is often composed of a human operator, a local master manipulator, and a remote slave manipulator, all connected by a communication network. Bilateral teleoperation systems (BTOS) include transmissions in both the forward and backward directions between the master and slave. This paper discusses a class of (BTOS) focusing on the security of the system after modeling the master and slave robots mathematically. The false data injection attack is examined, where the attacker may inject false data into the states that are being exchanged between the master and slave robots. The vulnerability of BTOS, where the attack destabilizes the system, is presented. A deep learning-based detection technique is proposed to detect the presence of false data injection attacks. The deep learning model with convolution neural network structure is trained and tested with considering complex attacks where the attacker has full knowledge of the system and proficiency to emanate and control the target system. The proposed model achieves 96\% validation accuracy, and the efficacy of the proposed deep learning detector is demonstrated and tested into the BTOS.

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“…where K d , K p , K dm ∈ R + . For the BTOS with a PD-like control method represented in Figure 9, the attacker can affect the system by FDI attacks, which can intelligently replace the signals (q T i , q T i ) T being exchanged by the robots with (q T i ,q T i ) T for i = m, s. For BTS, the DFDIA is discussed with respect to a specific form of storage function represented by ( 49 In 2016, Dong, Gupta and Chopra [150] For a BTOS with dynamics (47) controlled by (48). A FDI attack that changes the states being transmitted between the robots of the BTSs as ( 50):…”

Section: ❒ Issn: 2089-4856mentioning

confidence: 99%

Control of teleoperation systems in the presence of cyber attacks: A survey

Hamdan

Mahmoud

2021

IJRA

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<p>The teleoperation system is often composed of a human operator, a local master manipulator, and a remote slave manipulator that are connected by a communication network. This paper proposes a survey on feedback control design for the bilateral teleoperation systems (BTSs) in nominal situations and in the presence of cyber-attacks. The main idea of the presented methods is to achieve the stability of a delayed bilateral teleoperation system in the presence of several kinds of cyber attacks. In this paper, a comprehensive survey on control systems for BTSs under cyber-attacks is discussed. Finally, we discuss the current and future problems in this field.</p>

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False Data Injection Attacks in Bilateral Teleoperation Systems

Cited by 27 publications

References 23 publications

An Overview of Recent Advances of Resilient Consensus for Multiagent Systems under Attacks

An Overview of Recent Advances of Resilient Consensus for Multiagent Systems under Attacks

Deep Learning-based Attack Detector for Bilateral Teleoperation Systems

Control of teleoperation systems in the presence of cyber attacks: A survey

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