MedLocker: A Transferable Adversarial Watermarking for Preventing Unauthorized Analysis of Medical Image Dataset. (arXiv:2303.09858v1 [eess.IV])

The collection of medical image datasets is a demanding and laborious process
that requires significant resources. Furthermore, these medical datasets may
contain personally identifiable information, necessitating measures to ensure
that unauthorized access is prevented. Failure to do so could violate the
intellectual property rights of the dataset owner and potentially compromise
the privacy of patients. As a result, safeguarding medical datasets and
preventing unauthorized usage by AI diagnostic models is a pressing challenge.
To address this challenge, we propose a …

access adversarial analysis collection compromise datasets information intellectual property may medical patients personally identifiable information privacy process resources result rights unauthorized access watermarking