Abstract:

With the rapid development of various location-based services related applications,there is a service demand for counting the visiting users to a specific area of interest.Existing schemes realize the privacy protection of visiting users,but the encryption protocol used introduces a high computational overhead,which prevents real-time statistics on mobile users and suffers from the problem of misjudgment in different areas of interest.A new lightweight private location query scheme is proposed based on the bloom filter and scalar product computation.The proposed scheme designs a compound spatial bloom filter to efficiently encode location data,which,in combination with a secure scalar product computation protocol,allows service providers to learn whether a user is at a specific point of interest while preserving the user's location privacy.The proposed scheme can efficiently achieve the user’s position privacy access control while minimizing the overhead of computation and communication.Experimental results show that this scheme avoids the problem of user misjudgment in different areas of interest and improves the query accuracy compared with typical representative schemes;that under the set experimental conditions,the offline and online computational overheads can be reduced by two orders of magnitude,and that the scheme can reduce the communication overhead by about 50%.

Key words: location privacy, query privacy, bloom filter, secure scalar product