Privacy-preserving geo-tagged image search in edge–cloud computing for IoT

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of Information Security and Applications Pub Date : 2024-06-13 DOI:10.1016/j.jisa.2024.103808

Zongye Zhang, Fucai Zhou, Ruiwei Hou

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引用次数: 0

Abstract

The Internet of Things (IoT) generates a significant volume of geo-tagged images via surveillance sensors in edge–cloud computing environments. Image search is essential to facilitate information sharing, data analysis, and strategic decision-making. However, outsourced images are typically encrypted for privacy protection, posing a challenge in simultaneously searching for visual and geographical relevance on encrypted images. To address this, this paper proposes an edge intelligence empowered privacy-preserving top- $k$ geo-tagged image search scheme for IoT in edge–cloud computing. The scheme presents a novel single-to-multi searchable encryption method for geo-tagged images that enables multiple users to perform secure nearest neighbor queries on a data source. Additionally, an extended anchor-based position determination method and an inner product-based distance calculation method are designed to enable geo-tagged image similarity calculation on ciphertext. Finally, a secure pruning method is introduced to improve query performance. Experiments are conducted to verify the performance of the scheme in terms of high efficiency and accuracy of the search.

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物联网边缘云计算中的隐私保护地理标记图像搜索

物联网（IoT）通过边缘云计算环境中的监控传感器生成大量带有地理标记的图像。图像搜索对于促进信息共享、数据分析和战略决策至关重要。然而，为了保护隐私，外包图像通常都进行了加密，这给同时搜索加密图像的视觉和地理相关性带来了挑战。为解决这一问题，本文提出了一种边缘云计算物联网边缘智能保护隐私的 top-k 地理标记图像搜索方案。该方案提出了一种新颖的地理标记图像单对多搜索加密方法，使多个用户能够对一个数据源执行安全的近邻查询。此外，还设计了一种基于锚的扩展位置确定方法和一种基于内积的距离计算方法，以实现对密文的地理标记图像相似性计算。最后，还引入了一种安全剪枝方法来提高查询性能。实验验证了该方案在高效和准确搜索方面的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Information Security and Applications Computer Science-Computer Networks and Communications

CiteScore

10.90

自引率

5.40%

发文量

206

审稿时长

56 days

期刊介绍： Journal of Information Security and Applications (JISA) focuses on the original research and practice-driven applications with relevance to information security and applications. JISA provides a common linkage between a vibrant scientific and research community and industry professionals by offering a clear view on modern problems and challenges in information security, as well as identifying promising scientific and "best-practice" solutions. JISA issues offer a balance between original research work and innovative industrial approaches by internationally renowned information security experts and researchers.