Privacy-preserving outsourced image feature extraction

Dongmei Li; Xiaolei Dong; Zhenfu Cao; Haijiang Wang

doi:10.1016/j.jisa.2019.03.020

Privacy-preserving outsourced image feature extraction

Dongmei Li
, Xiaolei Dong^*
, Zhenfu Cao
, Haijiang Wang

^*此作品的通讯作者

软件工程学院

Shanghai University of Engineering Science
Zhejiang University of Science and Technology

科研成果: 期刊稿件 › 文章 › 同行评审

12 引用（Scopus）

摘要

Privacy-protected signal and image processing for outsourced computing has hence recently been popular. We present a framework for privacy-preserving outsourced image feature Extraction(POIFE) in the semi-honest setting. Also we prove that the construction is simulation-based secure under the semi-honest adversaries. In our scheme, the user can be flexible to outsource his computation to the cloud without real-time online. Compared with the previous works, our solution improves privacy.

源语言	英语
页（从-至）	59-64
页数	6
期刊	Journal of Information Security and Applications
卷	47
DOI	https://doi.org/10.1016/j.jisa.2019.03.020
出版状态	已出版 - 8月 2019

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10.1016/j.jisa.2019.03.020

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Privacy-preserving outsourced image feature extraction

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