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DriverAuth: A risk-based multi-modal biometric-based driver authentication scheme for ride-sharing platforms

机译:DriverAuth:基于风险的多模式基于生物特征的驾驶员身份验证方案

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摘要

On-demand ride and ride-sharing services have revolutionized the point-to-point transportation market and they are rapidly gaining acceptance among customers worldwide. Alone, Uber and Lyft are providing over 11 million rides per day (DMR, 2018a,b). These services are provided using a client-server infrastructure. The client is a smartphone-based application used for: (ⅰ) registering riders and drivers, (ⅱ) connecting drivers with riders, (ⅲ) car-sharing to share the expenses, minimize traffic congestion and saving traveling time, (ⅳ) allowing customers to book their rides. The server typically, run by multi-national companies such as Uber, Ola, Lyft, BlaBlaCar, manages drivers and customers registrations, allocates ride-assignments, sets tariffs, guarantees payments, ensures safety and security of riders, etc. However, the reliability of drivers have emerged as a critical problem, and as a consequence, issues related to riders safety and security have started surfacing. The lack of robust driver verification mechanisms has opened a room to an increasing number of misconducts (i.e., drivers subcontracting ride-assignments to an unauthorized person, registered drivers sharing their registration with other people whose eligibility to drive is not justified, etc.) (Horwitz, 2015; USAtoday, 2016). This paper proposes DriverAuth - a novel risk-based multi-modal biometric-based authentication solution, to make the on-demand ride and ride-sharing services safer and more secure for riders. DriverAuth utilizes three biometric modalities, i.e., swipe, text-independent voice, and face, in a multi-modal fashion to verify the identity of registered drivers. We evaluated DriverAuth on a dataset of 10,320 samples collected from 86 users and achieved a True Acceptance Rate (TAR) of 96.48% at False Acceptance Rate (FAR) of 0.02% using Ensemble Bagged Tree (EBT) classifier. Furthermore, the architecture used to design DriverAuth enables easy integration with most of the existing on-demand ride and ride-sharing systems.
机译:按需乘车和乘车共享服务彻底改变了点对点运输市场,并迅速赢得了全球客户的认可。单独,优步和Lyft每天提供超过1100万次游乐设施(DMR,2018a,b)。这些服务是使用客户端服务器基础结构提供的。客户端是基于智能手机的应用程序,用于:(ⅰ)注册车手和驾驶员,(ⅱ)将驾驶员与车手联系起来,(ⅲ)分享费用的共享汽车,最大程度地减少交通拥堵并节省出行时间,(ⅳ)允许客户预订游乐设施。该服务器通常由Uber,Ola,Lyft,BlaBlaCar等跨国公司运营,管理驾驶员和客户的注册,分配乘车分配,设置关税,保证付款,确保骑手的安全性等。但是,可靠性驾驶员已成为一个关键问题,结果,与骑手的安全性有关的问题开始浮出水面。缺乏健全的驾驶员核查机制,为越来越多的不当行为开辟了空间(例如,驾驶员将乘车分配分包给未经授权的人,注册的驾驶员与没有合法驾驶资格的其他人共享其注册信息等)( Horwitz,2015; USAtoday,2016)。本文提出了DriverAuth-一种新颖的基于风险的,基于多模式生物特征的身份验证解决方案,以使按需乘车和乘车共享服务更加安全和安全。 DriverAuth以多种方式使用三种生物识别方式,即滑动,独立于文本的语音和面部,以验证已注册驾驶员的身份。我们对从86个用户收集的10,320个样本的数据集进行了评估,使用整体袋装树(EBT)分类器以0.02%的错误接受率(FAR)实现了96.48%的真实接受率(TAR)。此外,用于设计DriverAuth的体系结构可轻松与大多数现有的按需乘车和乘车共享系统集成。

著录项

  • 来源
    《Computers & Security》 |2019年第6期|122-139|共18页
  • 作者

  • 作者单位

    Department of Information Engineering and Computer Science (DISI) University of Trento Italy;

    Department of Information Engineering and Computer Science (DISI) University of Trento Italy Department of Information Security KFUEIT Rahim Yar Khan Pakistan;

    Department of Information Engineering and Computer Science (DISI) University of Trento Italy Department of Computer Science (DISI) DistriNET KU Leuven Belgium;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Smartphone; Sensors; User authentication; Physiological and behavioral; biometrics; Risk-based approach;

    机译:手机;传感器;用户认证;生理和行为;生物识别;基于风险的方法;

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