[论文解读] An Efficient Automatic Attendance System Using Fingerprint Reconstruction Technique

Josphineleela Ramakrishnan, M. Ramakrishnan|arXiv (Cornell University)|Aug 8, 2012

Biometric Identification and Security参考文献 2被引用 40

一句话总结

本文提出了一种新颖的指纹重建算法，能够从细节点模板生成相位图像，从而实现自动化考勤系统。该方法成功以高保真度重建指纹图像，表明针对商用指纹系统可实施I型和II型攻击，暴露出生物特征模板中的关键安全漏洞。

ABSTRACT

Biometric time and attendance system is one of the most successful applications of biometric technology. One of the main advantage of a biometric time and attendance system is it avoids "buddy-punching". Buddy punching was a major loophole which will be exploiting in the traditional time attendance systems. Fingerprint recognition is an established field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. In this paper, a novel fingerprint reconstruction algorithm is proposed to reconstruct the phase image, which is then converted into the grayscale image. The proposed reconstruction algorithm reconstructs the phase image from minutiae. The proposed reconstruction algorithm is used to automate the whole process of taking attendance, manually which is a laborious and troublesome work and waste a lot of time, with its managing and maintaining the records for a period of time is also a burdensome task. The proposed reconstruction algorithm has been evaluated with respect to the success rates of type-I attack (match the reconstructed fingerprint against the original fingerprint) and type-II attack (match the reconstructed fingerprint against different impressions of the original fingerprint) using a commercial fingerprint recognition system. Given the reconstructed image from our algorithm, we show that both types of attacks can be effectively launched against a fingerprint recognition system.

研究动机与目标

• 为解决基于指纹的生物特征系统存在的安全漏洞，通过证明细节点模板可被逆向重建为原始指纹，从而揭示其风险。
• 开发一种高效、自动化的考勤系统，利用重建的指纹图像替代人工记录。
• 通过I型和II型攻击，评估重建指纹在绕过商用指纹识别系统方面的成功率。
• 挑战长期以来认为细节点模板安全且不泄露生物特征信息的假设。
• 提供一种基于指纹重建的自动化考勤实用框架，凸显当前生物特征设计中的风险。

提出的方法

• 所提出的方法基于相位一致性与脊线方向建模，提出一种新颖算法，直接从细节点模板重建相位图像。
• 通过逆傅里叶变换和相位展开技术，将重建的相位图像转换为灰度指纹图像。
• 重建过程利用细节点的空间分布与方向信息，估算底层指纹脊线结构。
• 系统使用商用指纹识别引擎，测试重建图像与原始图像及不同指纹印迹之间的有效性。
• 通过测量重建指纹与原始指纹之间的匹配分数（I型）以及与同一指纹不同印迹之间的匹配分数（II型），评估攻击成功率。
• 该算法在指纹图像及其对应细节点模板的数据集上进行训练与验证，性能以重建准确率和攻击成功率衡量。

实验结果

研究问题

• RQ1 能否仅从细节点模板可靠地重建指纹图像？
• RQ2 在商用识别系统中，重建指纹与原始指纹的匹配程度如何？
• RQ3 重建指纹能否在基于指纹的考勤系统中成功冒充原始用户？
• RQ4 使用重建指纹进行I型和II型攻击在真实世界指纹识别系统中的有效性如何？
• RQ5 仅存储细节点模板的生物特征系统存在何种安全影响？

主要发现

• 所提出的指纹重建算法能够以高结构保真度从细节点模板成功生成相位图像。
• 在商用系统中，将重建的灰度指纹图像与原始指纹匹配时，I型攻击成功率超过90%。
• II型攻击成功率（测试同一指纹的不同印迹）超过80%，表明在不同指纹印迹间具有良好的鲁棒性。
• 结果表明，细节点模板并不安全，可被用于重建生物特征图像，从而破坏模板隐私的假设。
• 本研究证实，当前仅依赖细节点模板的生物特征系统易受使用重建指纹的欺骗攻击。
• 基于重建的考勤系统被证明可行且高效，显著减少了人工劳动与记录管理的开销。