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A Dynamic Behavioral Biometric Approach to Authenticate Users Employing Their Fingers to Interact with Touchscreen Devices.

机译:一种动态行为生物识别方法,用于验证使用手指与触摸屏设备进行交互的用户。

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摘要

The use of mobile devices has extended to all areas of human life and has changed the way people work and socialize. Mobile devices are susceptible to getting lost, stolen, or compromised. Several approaches have been adopted to protect the information stored on these devices. One of these approaches is user authentication. The two most popular methods of user authentication are knowledge based and token based methods but they present different kinds of problems.;Biometric authentication methods have emerged in recent years as a way to deal with these problems. They use an individual's unique characteristics for identification and have proven to be somewhat effective in authenticating users. Biometric authentica-tion methods also present several problems. For example, they aren't 100% effective in identifying users, some of them are not well perceived by users, others require too much computational effort, and others require special equipment or special postures by the user. Ultimately their implementation can result in unauthorized use of the devices or the user being annoyed by the implementation.;New ways of interacting with mobile devices have emerged in recent years. This makes it necessary for authentication methods to adapt to these changes and take advantage of them. For example, the use of touchscreens has become prevalent in mobile devices, which means that biometric authentication methods need to adapt to it. One important aspect to consider when adopting these new methods is their acceptance of these methods by users. The Technology Acceptance Model (TAM) states that system use is a response that can be predicted by user motivation.;This work presents an authentication method that can constantly verify the user's identity which can help prevent unauthorized use of a device or access to sensitive information. The goal was to authenticate people while they used their fingers to interact with their touchscreen mobile devices doing ordinary tasks like vertical and horizontal scrolling. The approach used six biometric traits to do the authentication. The combination of those traits allowed for authentication at the beginning and at the end of a finger stroke. Support Vector Machines were employed and the best results obtained show Equal Error Rate values around 35%. Those results demonstrate the potential of the approach to verify a person's identity.;Additionally, this works tested the acceptance of the approach among participants, which can influence its eventual adoption. An acceptance level of 80% was obtained which compares favorably against other behavioral biometric approaches.
机译:移动设备的使用已扩展到人类生活的所有领域,并改变了人们的工作和社交方式。移动设备容易丢失,被盗或受损。已经采用了几种方法来保护存储在这些设备上的信息。这些方法之一是用户身份验证。用户身份验证的两种最流行的方法是基于知识的方法和基于令牌的方法,但是它们存在各种问题。生物特征身份验证方法是近年来出现的一种解决这些问题的方法。他们使用个人的独特特征进行识别,并被证明在验证用户身份方面有些有效。生物特征认证方法也存在一些问题。例如,它们在识别用户方面并不是100%有效的,其中一些没有被用户很好地感知,其他的则需要太多的计算工作,而其他的则需要用户使用特殊的设备或特殊的姿势。最终,它们的实现会导致设备的未授权使用,或者使实现使用户烦恼。近年来,出现了与移动设备进行交互的新方式。这使得身份验证方法必须适应这些更改并加以利用。例如,触摸屏的使用已在移动设备中普及,这意味着生物特征认证方法需要适应它。采用这些新方法时要考虑的一个重要方面是用户对这些方法的接受程度。技术接受模型(TAM)指出系统使用是可以由用户动机预测的响应;该工作提出了一种可以不断验证用户身份的身份验证方法,可以帮助防止未经授权使用设备或访问敏感信息。目的是在人们使用手指与执行垂直和水平滚动等普通任务的触摸屏移动设备进行交互时对他们进行身份验证。该方法使用六个生物特征进行身份验证。这些特征的组合允许在手指笔触的开始和结束时进行身份验证。使用支持向量机,获得的最佳结果显示相等错误率约为35%。这些结果证明了这种方法可以验证一个人的身份。此外,该作品测试了参与者对这种方法的接受程度,这可能会影响其最终采用。获得了80%的接受水平,与其他行为生物测定方法相比具有优势。

著录项

  • 作者

    Ponce, Arturo.;

  • 作者单位

    Nova Southeastern University.;

  • 授予单位 Nova Southeastern University.;
  • 学科 Computer science.;Bioinformatics.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 235 p.
  • 总页数 235
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:52:57

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