Research And Implementation Of The SNS-based Privacy Protection Technology

Social network named SNS, as one of the web2.0 technology products, has become the main platform that people can spread information and communication via the Internet. Its main activities are users and users’ relationship, using a lot of acts to strength and maintain this relationship. Social network is an information sharing platform and has saved mass of users’ attribute information and friend relationship data. With the popularity of social networking applications and the accumulation of personal information and the relationship data, it is a big challenge to protect private data under the condition of information sharing.This paper firstly studies the characteristics of social networks and the threat of privacy protection. Combining with the present situation of SNS privacy protection technology, this paper designs the privacy protection of user’ attribute information and customer’ relationship data.In view of the protection for user attributes, this paper come up with the idea of SNS fine-grained attribute anonymity algorithm, which implements the demand for users to choose their own attributes protection level. Due to the reduced number of anonymous attribute, the algorithm’s time complexity is lower than traditional ones. For the requirements of social network relational data privacy protection and availability, based on the traditional randomized algorithms of edge, a kind of safe and efficient social network privacy protection and access control scheme is put forward. It is concluded that the proposed algorithm that is the division of nodes and the randomization algorithm in social network group not only improves the degree of social network privacy protection also guarantee the availability of social network structure using map features significant constraints. The permissions control scheme combining the algorithm, speeds up the efficiency of authority to judge by permission transitivity.Finally, by constructing experiment simulation platform, measures the running time and information loss of the fine-grained attribute anonymity algorithm, the map features significant and efficiency of authority judging of the randomization algorithm in social network group. Analysis results show that, compared with existing randomization protection scheme based on edge, the scheme can efficiently protect the privacy of social network data and make the demand of protection and sharing of users’ attributes and relational data come true.