Abstract
In recent years, location-based services (LBS) have become very popular, especially with the rapid emergence of the Internet of Things (IoT). However, LBS introduces new security vulnerabilities, which can lead to violations of user privacy. Therefore, protecting user location privacy has become a growing concern. In this article, we investigate the privacy attack models on LBS users. Additionally, we present an in-depth review of current protection mechanisms. Moreover, we provide the comparison between these privacy preservation mechanisms to allow new research opportunities. Furthermore, we present our approach to protecting user privacy in LBS over Euclidean space. Then, we present the comparison of our approach with other works.
| Original language | English |
|---|---|
| Title of host publication | Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence |
| Publisher | River Publishers |
| Pages | 49-69 |
| Number of pages | 21 |
| ISBN (Electronic) | 9788770227773 |
| ISBN (Print) | 9788770227780 |
| Publication status | Published - Nov 11 2022 |
| Externally published | Yes |
Keywords
- Attack models.
- Location-based services
- Privacy preservation
- Security
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)
- Computer Science(all)