F-seeker:privacy-aware granular moving-object query framework based on over-anonymity

Aiming to the privacy-preserving problem for moving-object retrieval services in social network,we propose a granular friend retrieval framework based on over-anonymity,called F-Seeker.Before outsourcing data,we adopt an enhanced anonymity strategy--(k,m,e)-anonymity,which preserving user privacy from the curious retrieval service provider.In the processing of providing services,the service provider employs over-anonymity strategy based on visibility requirements to realize granular data access control.In addition,we encode data using Z-order address and the retrieval efficiency can be improved by pruning.Experimental results show that the proposed strategy can protect user privacy while the computation overhead does not increase greatly.