Privacy Disclosure Risk Analysis And Assessment In Location-Based Service

The popularity of mobile intelligent terminal has promoted the rapid development of Location-Based Service(LBS). The LBS is widely used to people's daily life and provides great convenience, brings a broad market and business opportunities. But it also brings the risk of privacy disclosure, the privacy disclosure of LBS has caused endless trouble to people's life, and seriously inhibited the development of LBS. So it's very urgent to assess the risk of LBS privacy disclosure. The risk assessment can provide recommendations for policy makers, security feedback for users, and increase people's confidence to LBS thereby. However, it has not yet been found for research on LBS privacy disclosure risk assessment at home and abroad. Based on this reason, this paper did research focuses on LBS privacy disclosure risk assessment system. This paper put forward two kinds of program for LBS privacy disclosure risk assessment, and initiated a precedent in the domain of LBS privacy disclosure risk assessment. The specific research contents of this paper are as follows:(1) Firstly, we set up the formal LBS privacy measure framework, and calculated the query privacy and location privacy based on attacker's inferred probability, and then get the amount of the loss in query privacy and location privacy; Secondly, we evaluated the value of privacy information. To calculate the value of LBS privacy disclosure risk by the amount of privacy disclosure and the value of privacy information. Through the above steps, we designed the method to LBS privacy disclosure risk assessment based on the privacy metric.(2) Firstly, we established the risk factor system through analyzing the privacy disclosure factors, and the membership matrix of risk factors was obtained by scoring the risk factors. Then generated the entropy weight coefficient from the membership matrix, and completed the first layer of fuzzy evaluation; Secondly, we computed the occurrence probability of risk factor from scoring the properties of risk factor, and achieved the second layer risk fuzzy evaluation from combining the results of the first layer with the occurrence probability of risk factor. Then we obtained the final value of the privacy disclosure risk. Through the above steps, we completed the assessment scheme to LBS privacy disclosure risk based on two level fuzzy comprehensive evaluation method.(3) We did the simulation experiment for the LBS privacy metric in the first program that we has designed, and the results show the effectiveness of the metric program. Then we realized the second program through simulation. In this part, we designed an application system for the LBS privacy disclosure risk assessment, the system was designed with visual operation interface. Finally, we did a simulation example in the system.