Optimal attack strategy for binary measurements-based Hammerstein system identification subject to data tampering attacks

Zimeng Zhou; Qingxiang Zhang; Fengwei Jing; Jin Guo; Zimeng Zhou; Qingxiang Zhang; Fengwei Jing; Jin Guo

doi:10.3934/era.2026197

Electronic Research Archive

2026, Volume 34, Issue 7: 4461-4485. doi: 10.3934/era.2026197

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Theory article

Optimal attack strategy for binary measurements-based Hammerstein system identification subject to data tampering attacks

1.
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
2.
National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing 100083, China

Received: 11 March 2026 Revised: 22 April 2026 Accepted: 08 May 2026 Published: 25 May 2026

This paper studies the formulation for an optimal attack strategy, which aims to maximize the identification error of Hammerstein systems with binary measurements subject to data tampering attacks. First, the convergence of the parameter estimates under attack is analyzed, and the absolute error between the estimated value and the true value is used as the objective function. Second, an optimization model with constraints on the maximum data tampering rate and the average data tampering rate is established to maximize the objective function. Then, the sine-cosine optimization algorithm is used to search for the optimal solution that meets the constraints, and its performance is compared with other algorithms. Finally, the effectiveness of the proposed method is verified by a numerical simulation.
- Hammerstein system,
- binary measurements,
- data tampering attack,
- optimal attack,
- optimization algorithm
Citation: Zimeng Zhou, Qingxiang Zhang, Fengwei Jing, Jin Guo. Optimal attack strategy for binary measurements-based Hammerstein system identification subject to data tampering attacks[J]. Electronic Research Archive, 2026, 34(7): 4461-4485. doi: 10.3934/era.2026197

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Abstract

This paper studies the formulation for an optimal attack strategy, which aims to maximize the identification error of Hammerstein systems with binary measurements subject to data tampering attacks. First, the convergence of the parameter estimates under attack is analyzed, and the absolute error between the estimated value and the true value is used as the objective function. Second, an optimization model with constraints on the maximum data tampering rate and the average data tampering rate is established to maximize the objective function. Then, the sine-cosine optimization algorithm is used to search for the optimal solution that meets the constraints, and its performance is compared with other algorithms. Finally, the effectiveness of the proposed method is verified by a numerical simulation.

References

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