Research On Location-based Privacy Protection In Mobile Social Network Applications

Nowadays,human society has entered the era of big data.Using big data to process,analyze,and solve problems has been widely used in the fields of military,medical and education.However,whether big data can be used safely and effectively has become a problem that current data privacy protection and information security researchers need to solve.The application of Location Based Services(LBS)has become a mainstream application in mobile social network applications.It can obtain the location information of mobile terminals through mobile smart devices with positioning system(such as GPS),providing users with many convenient services.However,location service information usually contains various privacy information of the user,such as the user's life track,personal habits and social situations,etc.which exposes the user to various risks of privacy disclosure and threatens the user's privacy information.Some literatures have proposed various solutions for the privacy protection of location information.However,due to the particularity of mobile social network applications,in order to obtain better services,users usually share location information for the convenience of exchange,and location information is transmitted through the mobile Internet,which brings new challenges to location privacy protection.This paper focuses on users' location privacy and query privacy disclosure issues in mobile social network applications.On the issue of location privacy,the privacy protection model based on l-diversity is used to protect the user's location data on the client and server respectively.On query privacy issues,the k-anonymity privacy query model is used to protect the user's location data and location query content information at the privacy protection processor and the location service provider respectively.Theoretical analysis and experimental results show that this method can effectively protect location privacy data and query data.The innovation points and work done in this paper are as follows:In the issue of the disclosure of the user's location privacy in mobile social network applications,when the user's location data table has a large number of quasi-identifier attribute dimensions,if the attribute dimension inferred as an attack reaches an exponential level,then the k-anonymity protection processing of the location data directly through generalization and hiding methods will lose a lot of location data,which in turn affects the availability of data.Based on the l-diversity protection model,the location data table is divided into a quasi-identifier attribute table and a sensitive attribute table,where the latitude and longitude of the user's location can be regarded as two sensitive attributes,and the privacy of the location data can be achieved through a lossy connection protection,to effectively reduce the loss of location data.The main work of this paper is to solve the problem of location privacy and query privacy disclosure of users in mobile social network applications.First,this paper addresses the issue of user location privacy disclosure in mobile social network applications.we propose a location privacy protection method for multi-sensitive attributes based on l-diversity privacy protection model,and protect the user's location information in client side and server respectively.On the client side,the decomposition algorithm of minimum distance grouping is used to lighten the location data,which makes the processed data satisfy the l₁-diversity principle and upload the data to the server in the form of QIT¹(Quasi-Identifier attribute Table)and ST¹(Sensitive attribute Table)to achieve the initial protection of the user's location data.On the server side,the minimum selection priority strategy is adopted to form the l₂-diversity group satisfying the multi-sensitive attributes,and the data is uploaded in the form of QIT² and ST² to further protect the user location data(where l₁< l₂).Second,this paper addresses the issue of user query privacy disclosure in mobile social network applications.We propose a k-anonymity based privacy query method for the privacy disclosure of location data and query content information in mobile social network applications.On the privacy protection processor side,an anonymous frame construction algorithm based on k-anonymity is proposed.Randomly selects a point near the longitude and latitude grid as the center O,selects the farthest point from the center O on the longitude and latitude grid as the initial radius R,and then construct the user's location data anonymous frame according to the user-defined privacy configuration to protect the location information when the user queries;In the location service providers,a location information query algorithm based on dynamic planning is proposed,which takes the center O of the anonymous frame of the location information of the query request user as the center,and obtains the region with the range of A,uses the idea of dynamic programming query algorithm to sort the Top-k to get the optimal answer tree,finally feeds back the query results to the privacy protection processor to realize the user's query content protection.