行为生物识别技术在数字银行中的自适应认证——防范完美的隐私

Supriya Lamba Sahdev, Saurabh Singh, Navleen Kaur, Laraibe Siddiqui
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引用次数: 3

摘要

本研究揭示了行为生物识别技术在数字银行领域的应用。在目前的情况下,与难以记录或模仿的心理/行为模式相比,更多的生理生物识别模式被用于数字银行,这使得行为生物识别技术更安全,可以抵御重放攻击。本研究建议使用手机屏幕滑动和触摸数据进行用户验证。实验使用公开可用的UMDAA02移动滑动数据集进行。研究结果为用于数字银行的移动设备的基于刷卡的认证系统提供了一个微调的功能集。已经观察到,使用建议的特征集,K-NN以14%的最佳EER优于Naïve bayes和SVM算法。由于K-NN所显示的这种性能,这项研究强烈表明,基于刷卡的身份验证系统可以用作数字银行系统的第二层安全保障。
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Behavioral Biometrics for Adaptive Authentication in Digital Banking - Guard Against Flawless Privacy
This study throws light on the usage of Behavioral Biometrics in Digital banking arena. In current scenario more of physiological biometric modalities are being used in Digital Banking in comparison to psychological/ behavioral modalities which are difficult to record or mimic making behavioral biometrics more secure against replay attacks. This study suggests the usage of mobile screen swipe and touch data for user verification. The experiments were performed using publicly available UMDAA02 mobile swipe data set. The results of the study present a fine-tuned feature set for a swipe-based authentication system for mobile devices used for Digital Banking. It has been observed that with the suggested feature set, K-NN outperforms Naïve bays and SVM algorithms with the best EER of 14%. With the kind of performance shown by K-NN this study strongly suggests, swipe-based authentication system that can be used as a secondary layer of security in the digital banking system.
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