基于属性基PIR的隐私保护云图像认证方案
首发时间:2022-09-27
摘要:针对云环境图像认证过程中潜在的泄露数据所有者以及用户图像特征隐私的问题,提出了一种基于属性基PIR的隐私保护的云图像认证方案。该方案借助属性基的隐私信息检索(Private Information Retrieval,PIR)完成密态环境下的隐私图像认证,一方面云服务器存储的由数据所有者提供的图像特征被加密,防止云服务器获取数据所有者隐私信息;另一方面用户在认证时并不需要提供明文的数据特征,并且所提供的加密属性特征也经过泛化处理,最大程度的保障用户隐私。最后,通过性能分析,在理论上证明了所提出的算法具有较好的隐私保护能力和算法执行效率,并且通过人脸和虹膜的公共数据集开展模拟实验测试,实验结果和成因分析进一步证明所提出方案相比于同类算法的优越性。
关键词: 隐私保护 云图像 图像认证 隐私信息检索 属性基加密
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Privacy preserving cloud image authentication scheme based on attribute based PIR
Abstract:In order to solve the potential problem of privacy of the owner in the process of graph authentication in cloud environment, a privacy protection scheme for cloud graph authentication based on attribute-based PIR was proposed.This scheme uses attribute based privacy information retrieval (PIR) to complete privacy graph authentication in the secret environment, so the graph features stored by the cloud server and provided by the data owner are encrypted and prevent the cloud server from obtaining the privacy information.On the other hand, the user does not need to provide the plaintext data characteristics during authentication and the encryption attribute characteristics also generalized to protect the user privacy.Finally, through the performance analysis, it is theoretically proved that this algorithm has better privacy protection ability and algorithm execution efficiency. Then experiments carried out through the public data set further proved the superiority of the proposed scheme.
Keywords: Privacy protection cloud graphs graph authentication privacy information retrieval attribute base encryption
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