Protecting Mobile Location Privacy Based On Public-key Cryptographic Algorithm

The development of sensor technology and mobile Internet has enabled the location based services. Location based services have become an indispensable part of people’s daily lives. However, they also bring some potential threats. Anonymization can provide a relatively high degree of privacy protection when we use these kinds of services, because it could avoid the information service provider directly contacting with the user’s sensitive information. To ensure the anonymity usage of location-based information services, accurate position information transmitted must not be easily re-confirm by the adversaries. There are many ways that we can use to achieve the anonymity of the position information to protect the user’s location privacy. However, due to the development of big data and data mining technologies, once accumulating a large number of query data, the server may get some laws of the trajectory, the laws can be used to infer a user’s trajectory based on the user’s behavior, thus all of the user’s track is leaking to the adversaries. In order to ensure the security and confidentiality of location based service. A mobile location privacy protection method based on public-key cryptography is presented. The model introduces a Confusion Server. Queries issued by the users will be encrypted with the Location Information Server’s public key. Then they will be forwarded by the Confusion Server to Location Information Server. After receiving a query request, the Location Information Server would use its own private key to decrypt the query, retrieval database to get the query results based on the mobile user’s location information, then encrypt the query results with the user’s public key in the query request. The encrypted query results would be sent to the user via Confusion Server, the user can decrypt the query results to complete a query. As the query is encrypted, the Confusion Server does not know the contents of the user’s query and the current location information. Location Information Server only knows the query, but doesn’t know user’s entity information, it couldn’t trace any user’s track. The experimental results show that the method is possible to protect the user’s location privacy better with marginal cost, finding a balance point between providing high-quality service and protecting the privacy of users. Under the premise of protecting the users’ privacy, the method could provide high quality services.