Privacy-Preserving Top-k Spatial Keyword Queries in Untrusted Cloud Environments

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Privacy-Preserving Top-k Spatial Keyword Queries in Untrusted Cloud Environments

Privacy-Preserving Top-k Spatial Keyword Queries in Untrusted Cloud Environments

Abstract

Privacy-Preserving Top-k Spatial Keyword Queries in Untrusted Cloud Environments, In recent years, spatial keyword queries have been widely used in various real-life applications with the rapid development of location-based services in mobile Internet.We study the privacy issue of top-k spatial keyword query in untrusted cloud environments.

Introduction

Privacy-Preserving Top-k Spatial Keyword We address this open problem by incorporating cloud computing power. Studying the privacy conservation scheme for top-k spatial keyword queries in outsourced environments is of great importance. Biometric identification is a task of finding the best match for a biometric trait by searching for biometric collections and further checking whether those two traits belong to the same person.

Projects on Privacy-Preserving Top-k Spatial Due to universality, uniqueness and permanence of biometric data, biometric identification has been more and more adopted as a way to identify and authenticate individuals with different systems.

It is thought to be a promising substitute for traditional identification approaches based on passwords and identification card. Despite the proliferation of biometric identification, as biometric data is highly sensitive and can not be revoked and replaced after leakage, there are also growing concerns about its associated privacy and legal issues.