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A White-Box Adversarial Attack Against a Digital Twin. (arXiv:2210.14018v1 [cs.CR])
Oct. 26, 2022, 1:24 a.m. | Wilson Patterson, Ivan Fernandez, Subash Neupane, Milan Parmar, Sudip Mittal, Shahram Rahimi
cs.CR updates on arXiv.org arxiv.org
Recent research has shown that Machine Learning/Deep Learning (ML/DL) models
are particularly vulnerable to adversarial perturbations, which are small
changes made to the input data in order to fool a machine learning classifier.
The Digital Twin, which is typically described as consisting of a physical
entity, a virtual counterpart, and the data connections in between, is
increasingly being investigated as a means of improving the performance of
physical entities by leveraging computational techniques, which are enabled by
the virtual counterpart. …
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