Abstract
Data detailed on Machine Learning have been presented. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, “Because machine learning models, especially black-box malicious models vulnerable to attribute inference attacks, are capable of generating a great deal of privacy leakage, recent work has focused on assessing these models in an attempt to prevent unexpected attribute privacy leakage. While there has been some success at model privacy risk evaluations, these traditional solutions are almost brittle in practice because they not only require white-box access to obtain model feature layer outputs but also their evaluation results are heavily influenced by the training dataset and the model structure, leading to difficulty in generalization."
NETL
NSTL
Elsevier