RQ-CEASE: A Resilient Quantized Collaborative Event-Triggered Average-Consensus Sampled-Data Framework Under Denial of Service Attack
Referred to as the RQ-CEASE, this article proposes a resilient framework for quantized, event-triggered (ET), sampled-data, average consensus in multiagent systems subject to denial of service (DoS) attacks. The DoS attacks typically attempt to block the measurement and communication channels in the...
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| Published in | IEEE transactions on systems, man, and cybernetics. Systems Vol. 51; no. 11; pp. 7027 - 7039 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2168-2216 2168-2232 |
| DOI | 10.1109/TSMC.2020.2965074 |
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| Abstract | Referred to as the RQ-CEASE, this article proposes a resilient framework for quantized, event-triggered (ET), sampled-data, average consensus in multiagent systems subject to denial of service (DoS) attacks. The DoS attacks typically attempt to block the measurement and communication channels in the network. Two different ET approaches are considered in RQ-CEASE based on whether the ET threshold is dependent or independent of the state dynamics. For each approach, we analytically derive operating conditions (bounds) for the sampling period and ET design parameter guaranteeing the input-to-state stability (ISS) of the network under DoS attacks. In addition, upper bounds for duration and frequency of DoS attacks are derived within which the network remains operational. For each approach, the maximum possible error from the average consensus value is derived. The resilience of the two RQ-CEASE approaches to DoS attacks, as well as their steady-state consensus error, and transmission savings are compared both analytically and using simulations. |
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| AbstractList | Referred to as the RQ-CEASE, this article proposes a resilient framework for quantized, event-triggered (ET), sampled-data, average consensus in multiagent systems subject to denial of service (DoS) attacks. The DoS attacks typically attempt to block the measurement and communication channels in the network. Two different ET approaches are considered in RQ-CEASE based on whether the ET threshold is dependent or independent of the state dynamics. For each approach, we analytically derive operating conditions (bounds) for the sampling period and ET design parameter guaranteeing the input-to-state stability (ISS) of the network under DoS attacks. In addition, upper bounds for duration and frequency of DoS attacks are derived within which the network remains operational. For each approach, the maximum possible error from the average consensus value is derived. The resilience of the two RQ-CEASE approaches to DoS attacks, as well as their steady-state consensus error, and transmission savings are compared both analytically and using simulations. |
| Author | Mohammadi, Arash Asif, Amir Amini, Amir |
| Author_xml | – sequence: 1 givenname: Amir surname: Amini fullname: Amini, Amir email: amir.amini@mail.concordia.ca organization: Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada – sequence: 2 givenname: Amir orcidid: 0000-0002-9393-7112 surname: Asif fullname: Asif, Amir email: amir.asif@mail.concordia.ca organization: Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada – sequence: 3 givenname: Arash orcidid: 0000-0003-1972-7923 surname: Mohammadi fullname: Mohammadi, Arash organization: Concordia Institute for Information Systems Engineering, Concordia University, Montreal, QC, Canada |
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| SubjectTerms | Collaboration Control systems Cyber-physical systems denial of service (DoS) attack Denial of service attacks Design parameters event-triggered (ET) consensus Monitoring Multiagent systems quantization Quantization (signal) Real-time systems Resilience resilient control Stability analysis Upper bounds |
| Title | RQ-CEASE: A Resilient Quantized Collaborative Event-Triggered Average-Consensus Sampled-Data Framework Under Denial of Service Attack |
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