On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models. (arXiv:2210.16258v1 [cs.CR])

Membership Inference Attacks (MIAs) infer whether a data point is in the
training data of a machine learning model. It is a threat while being in the
training data is private information of a data point. MIA correctly infers some
data points as members or non-members of the training data. Intuitively, data
points that MIA accurately detects are vulnerable. Considering those data
points may exist in different target models susceptible to multiple MIAs, the
vulnerability of data points under multiple …

attacks data data points target under vulnerability