Noninteractive Lightweight Privacy-Preserving Auditing on Images in Mobile Crowdsourcing Networks

Juan Zhang,Yongyong Chen,Xiaojun Guo,Chunyu Zhang,Changsheng Wan

doi:10.1155/2020/8827364

Abstract

To determine whether images on the crowdsourcing server meet the mobile user’s requirement, an auditing protocol is desired to check these images. However, before paying for images, the mobile user typically cannot download them for checking. Moreover, since mobiles are usually low-power devices and the crowdsourcing server has to handle a large number of mobile users, the auditing protocol should be lightweight. To address the above security and efficiency issues, we propose a novel noninteractive lightweight privacy-preserving auditing protocol on images in mobile crowdsourcing networks, called NLPAS. Since NLPAS allows the mobile user to check images on the crowdsourcing server without downloading them, the newly designed protocol can provide privacy protection for these images. At the same time, NLPAS uses the binary convolutional neural network for extracting features from images and designs a novel privacy-preserving Hamming distance computation algorithm for determining whether these images on the crowdsourcing server meet the mobile user’s requirement. Since these two techniques are both lightweight, NLPAS can audit images on the crowdsourcing server in a privacy-preserving manner while still enjoying high efficiency. Experimental results show that NLPAS is feasible for real-world applications.

Highlights

Mobile crowdsourcing systems have been widely deployed all over the world, which collect and process data through widely available mobile devices [1]
(2) We propose a novel auditing protocol called NLPAS, which can check whether the images stored on the CS meet the MU’s requirement
We have proposed a noninteractive lightweight privacy-preserving auditing protocol on images in mobile crowdsourcing networks called NLPAS

Summary

Introduction

Mobile crowdsourcing systems have been widely deployed all over the world, which collect and process data through widely available mobile devices [1]. Erefore, to ensure data trust, it is important to check whether the data collected by workers meet the mobile user’s requirement before using it [2]. We call this sort of protocol the auditing protocol. Erefore, to check images before downloading them, the auditing protocol should have the noninteractive feature. Erefore, the auditing protocol should have the privacy-preserving feature. Erefore, a noninteractive lightweight privacy-preserving auditing scheme is needed for the mobile user to check images before downloading them Due to limited resources of mobile users, the auditing protocol should be quite efficient. erefore, a noninteractive lightweight privacy-preserving auditing scheme is needed for the mobile user to check images before downloading them

Objectives

Methods

Conclusion