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A Robust Control Scheme for Time Delay Switch Attacks

Published: 15 November 2021 Publication History

Abstract

Modern manufacturing systems are increasingly vulnerable to cyber-attacks with a high level of automation and connectivity. Given that sensors are widely dependent upon to control manufacturing processes, the sensor-controller loop becomes an easy target for attacks. In this paper, a novel robust control framework is developed for systems subject to time delay switch (TDS) attacks, where data transmission from sensors to controllers are maliciously delayed. The attackers intend to make controllers use noncurrent information about the system states in order to destabilize and sabotage the system. Particularly, to increase the effectiveness of delay detection and prediction as well as error bound estimation for control, a new state space model based on diffeomorphism is formulated. A Markov chain model is developed to represent the TDS attacks. The uncertainty of system states is quantified and the upper bounds of delays are estimated. With the estimated bounds, a sliding integral mode control is developed to adjust the system to converge to the sliding manifold. The new framework is demonstrated with a 3D printer thermal control example.

Supplementary Material

MP4 File (AMSec21-fp05-Malashkhia.mp4)
Modern manufacturing systems are increasingly vulnerable to cyber-attacks with a high level of automation and connectivity. In this paper, a novel robust control framework is developed for systems subject to time delay switch (TDS) attacks, where data transmission from sensors to controllers are maliciously delayed. The attackers intend to make controllers use noncurrent information about the system states in order to destabilize and sabotage the system. Particularly, to increase the effectiveness of delay detection and prediction as well as error bound estimation for control, a new state space model based on diffeomorphism is formulated. A Markov chain model is developed to represent the TDS attacks. The uncertainty of system states is quantified and the upper bounds of delays are estimated. With the estimated bounds, a sliding integral mode control is developed to adjust the system to converge to the sliding manifold. The new framework is demonstrated with a 3D printer thermal control example.

References

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    cover image ACM Conferences
    AMSec '21: Proceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security
    November 2021
    72 pages
    ISBN:9781450384803
    DOI:10.1145/3462223
    © 2021 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the United States Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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    Published: 15 November 2021

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    Author Tags

    1. additive manufacturing
    2. control
    3. cyber-physical systems
    4. cybermanufacturing
    5. resilience
    6. time delay switch attack

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