论文标题
MSPPIR：云计算中的多源隐私图像检索
MSPPIR: Multi-source privacy-preserving image retrieval in cloud computing
论文作者
论文摘要
基于内容的图像检索（CBIR）技术已在诸如Google Images之类的云计算的帮助下进行了广泛的研究和服务。但是，这些图像总是包含丰富的敏感信息。在这种情况下，隐私保护成为一个大问题，因为云总是无法完全信任。已经提出了许多保留隐私图像检索方案，其中图像所有者可以将加密的图像上传到云中，所有者本人或授权用户可以在云的帮助下执行安全检索。然而，很少有现有的研究注意到更实用的多源场景。在本文中，我们分析了多源隐私图像检索的困难（MSPPIR）。然后，我们将jpeg-format中的图像作为示例，以提出一种称为JES-MSIR的方案，即一种新型的JPEG图像加密方案，该方案是为基于多源内容的图像检索而设计的。 JES-MSIR可以支持MSPPIR的要求，包括从多个来源获得的恒定回能检索以及多个来源的结合以获得更好的检索服务。实验结果和对拟议方案的安全性分析表明其效率，安全性和准确性。
Content-Based Image Retrieval (CBIR) techniques have been widely researched and in service with the help of cloud computing like Google Images. However, the images always contain rich sensitive information. In this case, the privacy protection become a big problem as the cloud always can't be fully trusted. Many privacy-preserving image retrieval schemes have been proposed, in which the image owner can upload the encrypted images to the cloud, and the owner himself or the authorized user can execute the secure retrieval with the help of cloud. Nevertheless, few existing researches notice the multi-source scene which is more practical. In this paper, we analyze the difficulties in Multi-Source Privacy-Preserving Image Retrieval (MSPPIR). Then we use the image in JPEG-format as the example, to propose a scheme called JES-MSIR, namely a novel JPEG image Encryption Scheme which is made for Multi-Source content-based Image Retrieval. JES-MSIR can support the requirements of MSPPIR, including the constant-rounds secure retrieval from multiple sources and the union of multiple sources for better retrieval services. Experiment results and security analysis on the proposed scheme show its efficiency, security and accuracy.
