A Survey on Privacy-Preserving Data Mining Methods
Yunlu Yang, Yajian Zhou · IOP Conference Series Materials Science and Engineering · 2020
Abstract In recent years, the increase in massive data in various fields has promoted the development of data mining. Still, the storage and mining of user data bring about the threat of privacy leakage. Researches on privacy-preserving data mining have become an increasingly significant research area. Focusing on the hidden dangers of privacy leakage in data mining methods, three leading privacy-preserving technologies came into being, which are data distortion technology, data encryption technology, and restricted publication technology. In this paper, we introduce and summarize the latest researches based on these privacy-preserving technologies. Besides, we describe the state-of-art research trends on privacy-preserving data mining methods in image processing and natural language processing.