Privacy Preservation of Semi-structured Data Based on XML

摘要

In the information age, people's various behavioral data are collected in large quantities. The sharing of information makes it convenient for some scientific investigations, but there is a leakage of personal privacy at the same time. The current research on privacy preservation is mostly based on relational tables or social network graphs. This paper focuses on semi-structured data, which is often ignored in privacy preservation. We propose a new privacy guarantee called X-k~m-anonymity and propose a bottom-up heuristic algorithm that provides protection by satisfying X-k~m-anonymity. We verified the feasibility of the algorithm through a reliable utility analysis method on the simulation data.