Design of a robust Controller/Observer for TCP/AQM network: First application to intrusion detection systems for drone fleet

Thierry Miquel 1 Jean-Philippe Condomines 1 Riad Chemali 1 Nicolas Larrieu 1
1 ENAC - Ecole Nationale de l'Aviation Civile
Abstract : This paper proposes a robust controller/observer for UAVs network anomaly estimation which is based on both Lyapunov Krasovkii functional and dynamic behavior of TCP (Transmission Control Protocol). Several research works on network anomaly estimation have been led using automatic control techniques and provide methods for designing both observer and command laws dedicated to time delay problem while estimating the anomaly or intrusion in the system. The observer design is based on a linearized fluid-flow model of the TCP behavior and must be associated to an AQM (Active Queue Management) to perform its diagnosis. The developed robust controller/observer in this paper has to be tuned by considering the time delay linear state-space representation of TCP model. As a first result, the designed controller/observer system has been successfully applied to some relevant practical problems such as topology network for aerial vehicles and the effectiveness is illustrated by using real traffic traces including Denial of Service attacks. Our first results show promising perspectives for Intrusion Detection System (IDS) in a fleet of UAVs.
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Communication dans un congrès
IROS 2017, EEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada. pp. 1707-1712, ISBN: 978-1-5386-2681-8 2017, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems 2017 (IROS’17)
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Soumis le : mardi 27 juin 2017 - 14:45:20
Dernière modification le : jeudi 22 février 2018 - 09:10:15
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Thierry Miquel, Jean-Philippe Condomines, Riad Chemali, Nicolas Larrieu. Design of a robust Controller/Observer for TCP/AQM network: First application to intrusion detection systems for drone fleet. IROS 2017, EEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada. pp. 1707-1712, ISBN: 978-1-5386-2681-8 2017, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems 2017 (IROS’17). 〈hal-01545617〉

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