Secure perception-driven control of mobile robots using chaotic encryption
This paper considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is subject to passive attacks and evasion attacks on image transmission. To defeat the passive attacks, we adopt chaotic encryption technique to di...
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Published in | IEEE transactions on automatic control Vol. 69; no. 4; pp. 1 - 8 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.04.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | This paper considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is subject to passive attacks and evasion attacks on image transmission. To defeat the passive attacks, we adopt chaotic encryption technique to disguise pixels of plain images in real time, and construct a bank of fuzzy unknown input observers to decrypt the cipher pixels in parallel. We characterize the security level of the proposed chaotic cryptographic scheme. As for the path tracking, we derive a set of LMI conditions of the existence of a robust controller, which renders the output zeroing manifold attractive and invariant by using internal model technique, and also attenuates the effects of the evasion attacks and learning errors of the machine learning system by reducing <inline-formula><tex-math notation="LaTeX">\mathcal {L}_{2}</tex-math></inline-formula> gain. Simulations are conducted in the CARLA simulator to demonstrate robust path tracking and secure image transmission. |
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AbstractList | This paper considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is subject to passive attacks and evasion attacks on image transmission. To defeat the passive attacks, we adopt chaotic encryption technique to disguise pixels of plain images in real time, and construct a bank of fuzzy unknown input observers to decrypt the cipher pixels in parallel. We characterize the security level of the proposed chaotic cryptographic scheme. As for the path tracking, we derive a set of LMI conditions of the existence of a robust controller, which renders the output zeroing manifold attractive and invariant by using internal model technique, and also attenuates the effects of the evasion attacks and learning errors of the machine learning system by reducing <inline-formula><tex-math notation="LaTeX">\mathcal {L}_{2}</tex-math></inline-formula> gain. Simulations are conducted in the CARLA simulator to demonstrate robust path tracking and secure image transmission. This article considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is subject to passive attacks and evasion attacks on image transmission. To defeat the passive attacks, we adopt chaotic encryption technique to disguise pixels of plain images in real time, and construct a bank of fuzzy unknown input observers to decrypt the cipher pixels in parallel. We characterize the security level of the proposed chaotic cryptographic scheme. As for the path tracking, we derive a set of linear matrix inequality (LMI) conditions of the existence of a robust controller, which renders the output zeroing manifold attractive and invariant by using internal model technique, and also attenuates the effects of the evasion attacks and learning errors of the machine learning system by reducing [Formula Omitted] gain. Simulations are conducted in the CARLA simulator to demonstrate robust path tracking and secure image transmission. |
Author | Zhu, M. Xu, S. Yuan, Z. Zhang, X. Lu, Y. |
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Snippet | This paper considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is... This article considers perception-driven control of a mobile robot for path tracking where perception is performed by a machine learning system. The robot is... |
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SubjectTerms | Algorithms Ciphers Cryptography Data models Encryption Image transmission Linear matrix inequalities Machine learning Mathematical analysis Mobile robots Path tracking Perception Pixels Robot control Robot sensing systems Robotic motion planning Robust control security |
Title | Secure perception-driven control of mobile robots using chaotic encryption |
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