Event-Triggered Resilient Consensus for Multi-Agent Networks Under Deception Attacks

Wu, Yiming; Xu, Ming; Zheng, Ning; He, Xiongxiong

doi:10.1109/access.2020.2989743

Cited by 23 publications

(15 citation statements)

References 42 publications

(76 reference statements)

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“…It does not need to be equipped with an additional attack detector to detect attacks as in [10], [20]. In [24], an event-triggered mechanism is introduced to reduce the impact of malicious attack. But if the malicious attack occurs when the event generator is not triggered, the agent will receive the deception signals such that the consensus performance may be reduced.…”

Section: Resultsmentioning

confidence: 99%

Leader-Following Consensus of Multiple Euler-Lagrange Systems Under Deception Attacks

et al. 2021

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In this paper, the leader-following consensus problem of a multi-Euler-Lagrange system is studied under deception attacks, where attackers can inject the false data into the data being exchanged over the communication network between two Euler-Lagrange systems. A distributed adaptive filter is proposed to compensate the unknown injection false data, where the magnitude of the false data is estimated. Meanwhile, the performance of the multiple Euler-Lagrange system consensus with the proposed filter can be guaranteed to be similar to that with the traditional controller when the communication network is not injected into false data by a malicious attacker. Furthermore, the consensus criteria of a multiple Euler-Lagrange system and the parameter design scheme of the proposed adaptive filter are achieved by using Lyapunov stability theory. Finally, a numerical example is carried out to demonstrate the effectiveness of the proposed consensus controller for a multi-Euler-Lagrange system attacked by using the false data injection.INDEX TERMS Euler-Lagrange systems, leader-following consensus, deception attack, distributed filter.

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Section: Resultsmentioning

confidence: 99%

Leader-Following Consensus of Multiple Euler-Lagrange Systems Under Deception Attacks

et al. 2021

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“…where α > 0 represents the rate new information replaces old information and K P , K I > 0 are the PI estimator gains. Remarkably, the latter constants play an important role in the convergence rate of estimator (12), as the the estimation dynamics is demanded to converge fast enough to provide a good approximation of ĉ = ĉ(t) (which is determined by each component of y, i.e. lim t→∞ |ĉ(t)−y i (t)| = 0 for i = 1, .…”

Section: B Robustness Of the Sbdcmentioning

confidence: 99%

“…In addition, the latter estimators are designed so that inputs c i,1 = ζ i and c i,2 = ζ 2 i feed their dynamics. The DPIA is therefore constituted by such a system interconnection between (23) and a couple of PI-ACEs (12). In the sequel, we employ network G within the two setups S1 and S2 described in the previous subsections.…”

Section: Numerical Examples On the Dpia Criticalitiesmentioning

confidence: 99%

“…Also, to the best of our knowledge, continuoustime MASs have not been studied by means of those tools yet. In [7], [12] part of the information being exchanged by the neighbors to a certain agent is chosen and then fully neglected via thresholding mechanisms. These selections are executed according to a given order that imposes some priority on the information itself to achieve attack mitigation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Secure Consensus via Objective Coding: Robustness Analysis to Channel Tampering

Fabris,

Zelazo

2021

Preprint

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This work mainly addresses continuous-time multiagent consensus networks where an adverse attacker affects the convergence performances of said protocol. In particular, we develop a novel secure-by-design approach in which the presence of a network manager monitors the system and broadcasts encrypted tasks (i.e. hidden edge weight assignments) to the agents involved. Each agent is then expected to decode the received codeword containing data on the task through appropriate decoding functions by leveraging advanced security principles, such as objective coding and information localization. Within this framework, a stability analysis is conducted for showing the robustness to channel tampering in the scenario where part of the codeword corresponding to a single link in the system is corrupted. A trade-off between objective coding capability and network robustness is also pointed out. To support these novelties, an application example on decentralized estimation is provided. Moreover, an investigation on robust agreement is as well extended in the discrete-time domain. Further numerical simulations are given to validate the theoretical results in both the time domains.

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“…Recently, there have been a growing number of research results on event-triggered control, the aim of which is to reduce the computational and communication burden while ensuring satisfactory system performance. [32] developed a distributed algorithm derived from the event-triggered strategy for achieving resilient consensus multi-agent networks under deception attacks. [33] proposed an eventtriggered control design that guarantees synchronization for output passive agents.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Resilient Average Consensus With Adversary Detection in the Presence of Byzantine Agents

Zhang

et al. 2021

IEEE Access

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This paper addresses the problem of resilient average consensus in the presence of Byzantine agents in multi-agent networks. An event-triggered secure acceptance and broadcasting algorithm is proposed in which full knowledge of the network and high computational capabilities of each regular node are not required. The computational expense and communication times are also reduced for the eventtriggered mechanism. We analyze the conditions for such a fully distributed algorithm to succeed in the flocal adversarial model. A new definition called an f-propagation graph, which is extended from rrobustness, turns out to be more accurate in describing the required topology conditions. Based on the proposed algorithm and topology conditions, we provide another algorithm to detect the adversarial nodes according to their abnormal behavior. When the network topology is an f-propagation graph, regular nodes that are equipped with the proposed algorithms update state values synchronously and eventually converge asymptotically to resilient average consensus. Simulation results are provided to verify the effectiveness of our proposed algorithms and the network topology conditions.INDEX TERMS Multi-agent networks, resilient consensus, adversary detection, event-triggered, Byzantine agents.

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Event-Triggered Resilient Consensus for Multi-Agent Networks Under Deception Attacks

Cited by 23 publications

References 42 publications

Leader-Following Consensus of Multiple Euler-Lagrange Systems Under Deception Attacks

Leader-Following Consensus of Multiple Euler-Lagrange Systems Under Deception Attacks

Secure Consensus via Objective Coding: Robustness Analysis to Channel Tampering

Event-Triggered Resilient Average Consensus With Adversary Detection in the Presence of Byzantine Agents

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