k‐anonymity based location privacy protection method for location‐based services in Internet of Thing

Abstract

The wide application of Internet of Things technology has promoted the application of location‐based services (LBS). Users can enjoy various conveniences brought by LBS. However, mobile users should submit their location information to LBS which may lead to privacy disclosure. Therefore, users need to protect their privacy while enjoying the service. If the privacy protection problem cannot be solved, the development of mobile internet business will be greatly affected. The existing location privacy protection methods take little account of real‐time road conditions and are unable to resist link attacks. In this article, a k‐anonymous location privacy protection method based on Voronoi map was proposed. First, the Voronoi diagram was divided according to road network structure and real‐time road network data, and Voronoi unit was established with the intersection as the base point. Then, the base point is sent as an anchor instead of the user's actual location to the third‐party server. The Voronoi diagram generated by the k‐anonymity constituted an anonymous space to resist multi‐query attacks and protected the location. k‐1 user location points that are communicating were selected to form k‐anonymous set with the current user, and send the anonymous set to LBS. Theoretical analysis and experimental results show that the proposed method not only efficiently protected location privacy, but also provided high‐quality service.

Performance, privacy and security issues at the TCP internet layer

“…Despite these challenges, TCP location-based services represent a crucial intersection of network technology and geographic information systems, offering significant benefits for both users and providers by delivering more personalized and location-aware online experiences. Studies have examined approaches like kanonymity spatial cloaking, and privacy-preserving location-based services to safeguard users' location privacy while still enabling the benefits of location-based applications [58], [59].…”

A K-Anonymous Location Privacy-Preserving Scheme for Mobile Terminals

“…To verify this problem, Tu et al [17]proposed a privacy preserving scheme to prevent semantic and re-identification attacks by employing three data masking methods: k-anonymity, l diversity and tcloseness. Wang et al [21] proposed a location privacy preservation method based on k-anonymity and Voronoi maps, which ensures the privacy of location information while guaranteeing the security of the process and highquality service.…”