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Experimental study of thumbprint-based authentication framework for ATM machines

机译:基于指纹的ATM机认证框架的实验研究

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The operation of Personal Identification Number (PIN) based Automated Teller Machine (ATM) has continued to experienced challenges currently militating against its acceptance and patronage. The challenges include card swallowing, misplacement, damage or expiration. Several users are also experiencing forgetfulness of PIN and the activities of fraudsters targeted at PIN pilfering for authorized access to account. This paper presents the experimental study of a framework for fingerprint authenticated ATM that addresses these challenges. The framework is an embodiment of different components for fingerprint processing which include enrollment, database and verification. Fingerprint enhancement, feature extraction and matching sub-modules form the verification component. The matching sub-modules rely on suitable mathematical models to function. The implementation was carried out using Windows 7 as operational platform while C# and Microsoft SQL server served as the frontend and backend engines respectively. The experimental study of the framework was performed with FVC2004, FVC2006 and FVC2008 standard databases and False Rejection Rate (FRR), False Acceptance Rate (FAR) and Average Matching Time (AMT) metrics were used for the evaluation. Obtained results were compared with those from similar and recently formulated algorithms.
机译:基于个人识别码(PIN)的自动柜员机(ATM)的操作一直面临挑战,目前阻碍了其接受和惠顾。挑战包括卡吞咽,错位,损坏或到期。一些用户还经历了PIN遗忘和欺诈者针对PIN盗窃以授权访问帐户的活动。本文介绍了针对指纹认证ATM的框架的实验研究,该框架解决了这些挑战。该框架是用于指纹处理的不同组件的实施例,包括注册,数据库和验证。指纹增强,特征提取和匹配子模块构成了验证组件。匹配的子模块依赖于合适的数学模型来起作用。该实现是使用Windows 7作为操作平台进行的,而C#和Microsoft SQL Server分别充当了前端和后端引擎。使用FVC2004,FVC2006和FVC2008标准数据库进行了框架的实验研究,并使用了错误拒绝率(FRR),错误接受率(FAR)和平均匹配时间(AMT)指标进行评估。将获得的结果与相似和最近制定的算法的结果进行比较。

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