Abstract: Biometric Identification（BI） is to identify an unknown individual by matching his biometric trait against a pre-established biometric database. In the era of E-service, BI has recently been widely used. As cloud computing is beginning more and more popular, BI can be aided with cloud service, which helps reduce the computation costs of the database owner. However, the connection of BI and cloud computing brings some new privacy concerns, such as leakage and unauthorized use of individuals’biometrics. This paper studis the problem of cloud based biometric identification. It firstly presents the security analysis of a recent scheme on BI outsourcing, and discloses its privacy flaws, then combines the techniques of data splitting and matrix transformation, and constructs an improved solution called EBIO. Theoretical analysis is presented to evaluate the proposal in terms of correctness and security. Lastly, the paper conducts extensive experiments on a prototype of the scheme. The experimental results show that the proposal is efficient and appropriate for practical use.

Key words: biometric identification, cloud computing, outsourcing computation, data security, privacy preserving

摘要： 生物识别是指将待识别个体的生物特征与预先成立的生物数据库进行匹配，从而完成个体身份识别的过程。目前，生物识别技术在互联网电子服务环境中得到了越来越广泛的应用。随着云计算的迅速发展，生物识别也可通过外包计算的方式提高识别效率。然而，这种计算外包模式同时带来了新的隐私风险，如个体生物特征信息的泄露以及被非授权的使用。主要对云计算环境中的生物识别外包方案展开研究。对最新的生物识别外包方案进行了安全性分析，并揭示了该方案存在的隐私漏洞；将数据拆分技术与矩阵变换相结合设计了新的数据隐私保护技术，提出了一个改进的生物识别外包方案EBIO；详细的理论分析论证了该方案的正确性和隐私性；对EBIO方案进行了原型实现并进行了大量实验。实验数据表明，EBIO方案可以高效地完成大规模生物识别任务，可在实际应用中进行实际部署。

关键词: 生物识别, 云计算, 外包计算, 数据安全, 隐私保护