| Title | A graph anonymity-based privacy protection scheme for smart city scenarios |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Luo, Man, Yan, Hairong |
| Conference Name | 2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) |
| Date Published | oct |
| Keywords | control theory, Fingerprint recognition, Graph Anonymity, graphical models, Human Behavior, human factors, location awareness, location information, location privacy, Personnel, privacy, pubcrawl, Real-time Systems, resilience, Resiliency, Scalability, smart cities |
| Abstract | The development of science and technology has led to the construction of smart cities, and in this scenario, there are many applications that need to provide their real-time location information, which is very likely to cause the leakage of personal location privacy. To address this situation, this paper designs a location privacy protection scheme based on graph anonymity, which is based on the privacy protection idea of K-anonymity, and represents the spatial distribution among APs in the form of a graph model, using the method of finding clustered noisy fingerprint information in the graph model to ensure a similar performance to the real location fingerprint in the localization process, and thus will not be distinguished by the location providers. Experiments show that this scheme can improve the effectiveness of virtual locations and reduce the time cost using greedy strategy, which can effectively protect location privacy. |
| Notes | ISSN: 2689-6621 |
| DOI | 10.1109/IAEAC54830.2022.9929671 |
| Citation Key | luo_graph_2022 |
A graph anonymity-based privacy protection scheme for smart city scenarios