Research On Location Anonymization And Nearest Neighbor Query Technology Supporting Privacy Preferences

With the development of mobile communication and space positioning technologies and the popularity of smart mobile terminals,location based services(LBS)have been widely applied in many areas,such as transportation,finance,security and so on.LBS bring convenience to people's lives,but also create privacy and security problems.The user needs to share his/her location in the process of obtaining services,but the location information contains much privacy information,such as user's behavior habits,religious beliefs,health status and so on.How to provide high-quality LBS services under the condition of guaranteeing user's privacy has become a research hotspot in the field of database and information security.Existing work lacks attention to user's preferences and can hardly support personalized queries.In this thesis,we consider the problem of user's preferences in location privacy-preserving k nearest neighbor queries.The main contributions are summarized as follows:(1)The characteristics of existing location privacy-preserving k nearest neighbor query technologies and the commonly used means of location privacy attack are thoroughly analyzed.The problems and solutions of k nearest neighbor queries are discussed from the aspect of the query internal mechanism.(2)To deal the problems of the location privacy-preserving k nearest neighbor query methods based on location disturbance in European space,such as heavy query overhead and the uncontrollability of query process and privacy,a Feedback Angle based location Privacy-preserving k Nearest neighbor query method(FAPN)is proposed.The concept of the feedback angle is introduced and the query processing regulation mechanism based on feedback angle is constructed.In this way,the query performance can be improved and the user can regulate the query performance and privacy.(3)Existing location privacy-preserving k nearest neighbor query methods on road networks can not provide sufficient location privacy preserving against replay attack,as well as regulation mechanisms of anonymization performance,query performance and privacy.To deal with the aforementioned problems,a Cloaking Circle based Privacy-preserving k Nearest neighbor query on road networks(CCPN)is proposed.The termination condition of the subnet construction can be set based on the probability distribution of the road network cicle in the location anonymization stage.In this way,the replay attack can be efficiently resisted.Besides,the scale of the anonymous subnet can be regulated by setting appropriate termination condition,which can provide the function of regulating the anonymization performance,query performance and privacy.What's more,the query efficiency is improved according to the characteristic of the anonymous subnet.Theoretical analysis and experimental results demonstrate that the proposed methods are effective and efficient.