当前位置: X-MOL 学术IEEE Trans. Inform. Forensics Secur. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Efficient Known-Sample Attack for Distance-Preserving Hashing Biometric Template Protection Schemes
IEEE Transactions on Information Forensics and Security ( IF 6.8 ) Pub Date : 2021-04-16 , DOI: 10.1109/tifs.2021.3073802
Yenlung Lai , Zhe Jin , KokSheik Wong , Massimo Tistarelli

The rapid deployment of biometric authentication systems raises concern over user privacy and security. A biometric template protection scheme emerges as a solution to protect individual biometric templates stored in a database. Among all available protection schemes, a template protection scheme that relies on distance-preserving hashing has received much attention due to its simplicity and efficiency in offering privacy protection while archiving decent authentication performance. In this work, we introduce an efficient attack called known sample attack and demonstrate that most state-of-art template protection schemes that utilize distance-preserving hashing can be compromised in practice (within few seconds), especially when the output is significantly smaller than the original input sample size. These findings further motivated our subsequent work in proposing a secure authentication mechanism to resist such an attack with proper study over the distribution of the input samples. Furthermore, we conducted revocability, unlinkability analysis to demonstrate the satisfactory of general biometric template protection requirements; and showed the resistance of various security and privacy attacks, i.e., false acceptance attack, and attack via record multiplicity.

中文翻译:

保留距离的哈希生物特征模板保护方案的有效已知样本攻击

生物特征认证系统的快速部署引起了对用户隐私和安全性的关注。生物特征模板保护方案作为保护数据库中存储的各个生物特征模板的解决方案而出现。在所有可用的保护方案中,依赖于保留距离的哈希的模板保护方案由于其在归档体面的身份验证性能时提供隐私保护的简单性和效率而受到了广泛的关注。在这项工作中,我们介绍了一种称为已知样本攻击的有效攻击,并演示了在实践中(几秒钟之内)会损害大多数利用距离保留哈希的最新模板保护方案,尤其是当输出显着小于原始输入样本大小。这些发现进一步激发了我们随后的工作,即通过对输入样本的分布进行适当的研究,提出一种安全的身份验证机制来抵抗这种攻击。此外,我们进行了可撤销性,不可链接性分析,以证明满足一般生物识别模板保护要求;并展示了各种安全和隐私攻击(例如,错误接受攻击和通过记录多重性攻击)的抵抗力。
更新日期:2021-05-25
down
wechat
bug