Abstract
The widespread use of Internet of Things (IoT) technology has promoted location‐based service (LBS) applications. Users can enjoy various conveniences brought by LBS by providing location information to LBS. However, it also brings potential privacy threats to location information. Location data that contains private information is often transmitted among IoT networks in LBS, and such privacy information should be protected. In order to solve the problem of location privacy leakage in LBS, a location privacy protection scheme based on k‐anonymity is proposed in this paper, in which the Geohash coding model and Voronoi graph are used as grid division principles. We adopt the client‐server‐to‐user (CS2U) model to protect the user’s location data on the client side and the server side, respectively. On the client side, the Geohash algorithm is proposed, which converts the user’s location coordinates into a Geohash code of the corresponding length. On the server side, the Geohash code generated by the user is inserted into the prefix tree, the prefix tree is used to find the nearest neighbors according to the characteristics of the coded similar prefixes, and the Voronoi diagram is used to divide the area units to complete the pruning. Then, using the Geohash coding model and the Voronoi diagram grid division principle, the G‐V anonymity algorithm is proposed to find k neighbors in an anonymous area so that the user’s location data meets the k‐anonymity requirement in the area unit, thereby achieving anonymity protection of location privacy. Theoretical analysis and experimental results show that our method is effective in terms of privacy and data quality while reducing the time of data anonymity.
Highlights
With the rapid development of the Internet of Things (IoT), mobile computing, GPS, and wireless communication technology, location-based service (LBS) has been widely used in many important fields [1,2,3,4]
(2) On the server side, the user-generated Geohash code is inserted into the prefix tree, the prefix tree is used to find the nearest neighbors according to the characteristics of the coded similar prefixes, and the Voronoi diagram is used to divide the area units to complete the pruning
We propose a location privacy protection method for road networks based on k-anonymity, in which the Geohash coding model and Voronoi graph are used as grid division principles
Summary
With the rapid development of the Internet of Things (IoT), mobile computing, GPS, and wireless communication technology, location-based service (LBS) has been widely used in many important fields [1,2,3,4]. Based on Geohash coding and the Voronoi diagram, this paper proposes a road network-oriented location privacy protection method (G-V anonymity algorithm). It can ensure privacy protection, improve the quality of service and the availability of published data, and reduce the time of data anonymity. The advantages of the prefix tree are as follows: use the common prefix of the string to reduce the query time, minimize the unnecessary string comparison, and the query efficiency is higher than the hash tree (3) Based on the Geohash coding model and Voronoi diagram grid generation principle, this paper proposes the G-V anonymity algorithm, which can find k neighbors in the anonymous area and make the user’s location data meet the k-anonymity requirement in the area unit, so as to protect the location privacy.
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