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Cloud-assisted secure biometric identification with sub-linear search efficiency
Soft Computing ( IF 4.1 ) Pub Date : 2019-10-04 , DOI: 10.1007/s00500-019-04401-9
Youwen Zhu , Xingxin Li , Jian Wang , Jing Li

Abstract

Cloud computing has been one of the critical solutions to reduce heavy storage and computation burden of biometric identification. To protect the privacy of biometric data against untrusted cloud servers, outsourced biometric databases are usually encrypted by users. Performing biometric identification over encrypted data without revealing privacy to cloud servers attracts more and more attention. Several secure biometric identification solutions have been proposed to solve this challenging problem. However, these schemes still suffer from various limitations, such as low search efficiency and heavy computation burden on users. In this paper, we propose a novel cloud-assisted biometric identification scheme based on the asymmetric scalar-product preserving encryption (ASPE) and spatial data structures such as the R-tree index, which simultaneously achieves sub-linear search efficiency and low computation burden on users. Specifically, we construct an R-tree index on the biometric dataset and encrypt the index with ASPE. Then we modify the original search algorithm in the R-tree index and design a secure search algorithm based on ASPE to find the nearest neighbor result over the encrypted R-tree index. Through theoretical analysis and extensive experiments, we demonstrate the effectiveness and efficiency of our proposed approach.



中文翻译:

具有亚线性搜索效率的云辅助安全生物识别

摘要

云计算一直是减少生物识别的繁重存储和计算负担的关键解决方案之一。为保护生物特征数据不受不受信任的云服务器的侵害,通常由用户对外包的生物特征数据库进行加密。在不向云服务器透露隐私的情况下对加密数据执行生物特征识别引起了越来越多的关注。已经提出了几种安全的生物特征识别解决方案来解决这个具有挑战性的问题。但是,这些方案仍然遭受各种限制,例如搜索效率低和用户的计算负担重。在本文中,我们提出了一种基于非对称标量积保密码(ASPE)和R-tree索引等空间数据结构的新型云辅助生物识别方案。同时实现亚线性搜索效率和较低的用户计算负担。具体来说,我们在生物识别数据集上构建R树索引,并使用ASPE对索引进行加密。然后,我们修改了R-tree索引中的原始搜索算法,并设计了一种基于ASPE的安全搜索算法,以在加密的R-tree索引上找到最近的邻居结果。通过理论分析和广泛的实验,我们证明了我们提出的方法的有效性和效率。然后,我们修改了R-tree索引中的原始搜索算法,并设计了一种基于ASPE的安全搜索算法,以在加密的R-tree索引上找到最近的邻居结果。通过理论分析和广泛的实验,我们证明了我们提出的方法的有效性和效率。然后,我们修改了R-tree索引中的原始搜索算法,并设计了一种基于ASPE的安全搜索算法,以在加密的R-tree索引上找到最近的邻居结果。通过理论分析和广泛的实验,我们证明了我们提出的方法的有效性和效率。

更新日期:2020-03-24
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