Privacy Policy Negotiation Method Research And Realization Based On User And Services Characteristics In M-commerce Environment

With the rapid development of the mobile services industry,security issues are more and more serious in mobile terminal and privacy concerns restrict the promotion and applications of M-commerce seriously.At present,a privacy policy is regarded as an effective way to protect personal privacy information and it has been adopted by the vast majority of mobile service providers.However,the current privacy policy is unilaterally developed by mobile service providers,ignoring the user's personalized privacy preferences and dynamic service needs.This one-way,static and hard-to-understand privacy policy is not suitable for a wide range of services and personalized service.Therefore,under the M-commerce,it is urgent to explore both efficient negotiation and conflict mitigation methods to alleviate the privacy concerns of mobile users,improving the protection of privacy and promoting the healthy development of M-commerce.In this paper,two models and corresponding algorithms for the privacy policy negotiation have been proposed from user and service characteristics,which are discussed below:(1)For the scenario of M-commerce applications used for the first time,it recommends privacy policy according to user characteristics.Under the guidance of many empirical researches,a privacy policy negotiation model is developed based on personalized recommendations combining with the objective technology and user subjective perception.Considering the user characteristics and privacy preferences,in the model we designed a privacy heterogeneity evaluation algorithm and a privacy policy personalized recommendation algorithm to realize personalized recommendation interactive privacy policy negotiation process by information generalization technology,privacy compromise value and three-interval fuzzy method.In the Eclipse&Android 4.4 platform,we developed a privacy policy negotiation method with personalized recommendation prototype system,proving that this method is more effective to reduce the user's privacy concerns and improve the user's willingness to disclose information when comparing with the traditional privacy policy.(2)For the scenario of M-commerce applications used once again,we established a mobile service-based privacy policy Petri Net(SPPN).Considering the user dynamic service expectation,it describes the privacy policy to serve as fine granularity rather than as a whole.On this basis,the SPPN negotiation algorithm is proposed to achieve the two-stage process of privacy policy negotiation and conflict detection.It supports service providers and users to negotiate privacy policy for service Taking "Taobao" and "VIP" as the research examples,the results show that this method can improve the negotiation efficiency and the negotiation success rate compared with the traditional method.