| Title | An Efficient Location Privacy Preserving Model based on Geohash |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Xiang, Wei |
| Conference Name | 2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) |
| Keywords | data privacy, efficient location privacy preserving model, Geohash coding, Geohash geographic information, great convenience, great hidden trouble, k-anonymity, LBS privacy protection model, location based services, location-aware mobile devices, Location-based service, location-based services, Metrics, mobile computing, privacy models and measurement, Privacy protection model, pubcrawl, query processing, user privacy security |
| Abstract | With the rapid development of location-aware mobile devices, location-based services have been widely used. When LBS (Location Based Services) bringing great convenience and profits, it also brings great hidden trouble, among which user privacy security is one of them. The paper builds a LBS privacy protection model and develops algorithm depend on the technology of one dimensional coding of Geohash geographic information. The results of experiments and data measurements show that the model the model has reached k-anonymity effect and has good performance in avoiding attacking from the leaked information in a continuous query with the user's background knowledge. It also has a preferable performance in time cost of system process. |
| DOI | 10.1109/BESC48373.2019.8963346 |
| Citation Key | xiang_efficient_2019 |
An Efficient Location Privacy Preserving Model based on Geohash