Privacy Protection in Mobile Social Network in the Context of Big Data

摘要

With the rapid development of Web 2.0 technology, mobile social network data has shown the classical big data characteristics. The analysis of social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. A series of privacy preserving models and algorithms for social network data are proposed. In this paper, we summarized the privacy leakage type of social network, such as attacks on social network nodes and edges, deeply analyzed the existing privacy preserving technology from the following aspects: node K-anonymity, sub-graph K-anonymity, and data disturbance, pointed out its advantages and disadvantages, and prospected the future research directions from four aspects.