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IEEE/ICACT20250208 Slide.19        [Big Slide]       [YouTube]	Oral Presentation
	This work assesses state estimation methods for autonomous EV digital twin systems under cyberattack, explicitly evaluating the flexibility of EKF, UKF, and PF against FDI and DoS attacks. The findings emphasize that EKF and UKF perform better than PF in terms of state estimation precision, remarkably when handled with cyber threats. This is due to their capacity to better dominate nonlinearities and approach dynamics. Additionally, we will try to include more attacks on EV systems, and do penetration testing using machine learning algorithms. We will try to make some recommendations based on these type of analysis and findings. Hopefully, this can help to the EV community, industries, research and development.

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