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Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution › peer-review

Standard Standard

Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. / Ahmad, Saif; Ahmed, Hafiz.
2022 IEEE Texas Power and Energy Conference (TPEC). IEEE, 2022. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution › peer-review

HarvardHarvard

Ahmad, S & Ahmed, H 2022, Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. in 2022 IEEE Texas Power and Energy Conference (TPEC). IEEE, pp. 1-6. https://doi.org/10.1109/TPEC54980.2022.9750751

APA

Ahmad, S., & Ahmed, H. (2022). Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. In 2022 IEEE Texas Power and Energy Conference (TPEC) (pp. 1-6). IEEE. https://doi.org/10.1109/TPEC54980.2022.9750751

CBE

Ahmad S, Ahmed H. 2022. Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. In 2022 IEEE Texas Power and Energy Conference (TPEC). IEEE. pp. 1-6. https://doi.org/10.1109/TPEC54980.2022.9750751

MLA

Ahmad, Saif and Hafiz Ahmed "Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach". 2022 IEEE Texas Power and Energy Conference (TPEC). IEEE. 2022, 1-6. https://doi.org/10.1109/TPEC54980.2022.9750751

VancouverVancouver

Ahmad S, Ahmed H. Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. In 2022 IEEE Texas Power and Energy Conference (TPEC). IEEE. 2022. p. 1-6 doi: https://doi.org/10.1109/TPEC54980.2022.9750751

Author

Ahmad, Saif ; Ahmed, Hafiz. / Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach. 2022 IEEE Texas Power and Energy Conference (TPEC). IEEE, 2022. pp. 1-6

RIS

TY - CHAP

T1 - Robust Intrusion Detection for Resilience Enhancement of Industrial Control Systems: An Extended State Observer Approach

AU - Ahmad, Saif

AU - Ahmed, Hafiz

PY - 2022/4/14

Y1 - 2022/4/14

N2 - We address the problem of attack signal estimation in industrial control systems that are subjected to actuator false data injection attack (FDIA) and where the sensor measurements are corrupted by non-negligible high-frequency measurement noise. The actuator FDIA signal is categorized as disturbance to be estimated and subsequently compensated, based on the concept of extended state observer (ESO). We investigate the efficacy of two alternatives to conventional ESO namely, cascade ESO (CESO) and low-power higher-order ESO (LHESO), that guarantee improved estimation performance in case of noisy measurement data as well as time-varying attack signals. Simulation results under different types of FDIAs demonstrate the advantages of designed schemes in comparison to conventional linear and nonlinear ESOs, using network motion control system as an illustrative example.

AB - We address the problem of attack signal estimation in industrial control systems that are subjected to actuator false data injection attack (FDIA) and where the sensor measurements are corrupted by non-negligible high-frequency measurement noise. The actuator FDIA signal is categorized as disturbance to be estimated and subsequently compensated, based on the concept of extended state observer (ESO). We investigate the efficacy of two alternatives to conventional ESO namely, cascade ESO (CESO) and low-power higher-order ESO (LHESO), that guarantee improved estimation performance in case of noisy measurement data as well as time-varying attack signals. Simulation results under different types of FDIAs demonstrate the advantages of designed schemes in comparison to conventional linear and nonlinear ESOs, using network motion control system as an illustrative example.

KW - actuator false data injection attack

KW - extended state observer

KW - industrial control system

KW - measurement noise

U2 - https://doi.org/10.1109/TPEC54980.2022.9750751

DO - https://doi.org/10.1109/TPEC54980.2022.9750751

M3 - Other chapter contribution

SP - 1

EP - 6

BT - 2022 IEEE Texas Power and Energy Conference (TPEC)

PB - IEEE

ER -