Trajectory Privacy Protection Method Based on Location Service in Fog Computing
| Autor: | Shuaishuai Zhao, Guangshun Li, Junhua Wu, Dandan Lin, Yanmin Yin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Privacy protection 020206 networking & telecommunications Cloud computing 02 engineering and technology Bottleneck Fog computing Location-based service 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing business Internet of Things General Environmental Science Computer network Anonymity |
| Zdroj: | Procedia Computer Science. 147:463-467 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2019.01.273 |
| Popis: | With the development of cloud computing in the Internet of Things and the wide application based on location services, the location trajectory information of mobile users is increasing. The risk of privacy leakage is also increasing. In order to protect the user’s trajectory privacy in the location service, we have designed a trajectory privacy protection method with several properties in the fog-based architecture. Fog computing extends the capabilities of cloud computing to the edge of the network, with local computing and storage capabilities, and a wide geographical mobility. Therefore, this paper uses the fog server instead of the traditional TTP anonymous server in the location-based privacy protection to solve the problem that performance bottleneck and concentrated attack in the TTP server anonymity process, and then completes our design with several properties through the fog server. The TRT algorithm implements k-anonymity of the trajectory. Finally, experimental analysis proves that our method can effectively enhance the user’s trajectory privacy. |
| Databáze: | OpenAIRE |
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