当前位置: X-MOL 学术Soft Comput. › 论文详情
Cloud-assisted secure biometric identification with sub-linear search efficiency
Soft Computing ( IF 2.784 ) 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.
更新日期:2020-03-24

 

全部期刊列表>>
宅家赢大奖
向世界展示您的会议墙报和演示文稿
全球疫情及响应:BMC Medicine专题征稿
新版X-MOL期刊搜索和高级搜索功能介绍
化学材料学全球高引用
ACS材料视界
x-mol收录
自然科研论文编辑服务
南方科技大学
南方科技大学
西湖大学
中国科学院长春应化所于聪-4-8
复旦大学
课题组网站
X-MOL
香港大学化学系刘俊治
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug