  In the big data era, many organizations face the dilemma of data sharing.
Regular data sharing is often necessary for human-centered discussion and
communication, especially in medical scenarios. However, unprotected data
sharing may also lead to data leakage. Inspired by adversarial attack, we
propose a method for data encryption, so that for human beings the encrypted
data look identical to the original version, but for machine learning methods
they are misleading. To show the effectiveness of our method, we collaborate
with the Beijing Tiantan Hospital, which has a world leading neurological
center. We invite $3$ doctors to manually inspect our encryption method based
on real world medical images. The results show that the encrypted images can be
used for diagnosis by the doctors, but not by machine learning methods.
