Comparison of machine learning models applied on anonymized data with different techniques. (arXiv:2305.07415v1 [cs.LG])

Anonymization techniques based on obfuscating the quasi-identifiers by means
of value generalization hierarchies are widely used to achieve preset levels of
privacy. To prevent different types of attacks against database privacy it is
necessary to apply several anonymization techniques beyond the classical
k-anonymity or $\ell$-diversity. However, the application of these methods is
directly connected to a reduction of their utility in prediction and decision
making tasks. In this work we study four classical machine learning methods
currently used for classification …

anonymity anonymized data attacks beyond data database diversity machine machine learning machine learning models privacy techniques types value