Survey on Approaches Developed for Preserving Privacy of Data Objects

In this paper, the authors review methods to secure objects for the past 30 years. Data disclosure preventing techniques such as uncertainty function and two data transformation technique are depicted. Privacy homomorphism and encryption methods such as Commercial Data Masking Facility algorithm (CDMF), markov-like perturbation and decryption of perturbation are also discussed in detail. The knowledge discovery data mining techniques to preserve privacy such as generalization and suppression are elaborately studied. Partition-and-group framework for clustering trajectories traclus algorithm, natural spatio-temporal operators are also elaborately studied.

Resource Details

Provided by:
International Advanced Research Journal in Science, Engineering and Technology (IARJSET)
Data Management