Releasing full data records is one of the most challenging problems in data privacy. On the
one hand, many of the popular techniques such as data de-identification are problematic
because of their dependence on the background knowledge of adversaries. On the other
hand, rigorous methods such as the exponential mechanism for differential privacy are often
computationally impractical to use for releasing high dimensional data or cannot preserve
high utility of original data due to their extensive data perturbation. This paper presents a …

In the field of privacy protection, publishing complete data (especially high-dimensional data
sets) is one of the most challenging problems. The common encryption technology can not
deal with the attacker to take differential attack to obtain sensitive information, while the
existing differential privacy protection algorithm model takes a long time for high-
dimensional calculation and needs to add noise to reduce data accuracy, which is not
suitable for high-dimensional large data sets. In view of this situation, this paper designs a …