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Double serial adaptation mechanism for keystroke dynamics authentication based on a single password

机译:基于单个密码的按键动态验证双重串行适配机制

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摘要

Cyber-attacks have spread all over the world to steal information such as trade secrets, intellectual property and banking data. Facing the danger of the insecurity of saved data (personal, professional, official, etc.), keystroke dynamics was proposed as an interesting, non-intrusive, inexpensive, permanent and weakly constrained solution for users. Based on the typing rhythm of users, it improves logical access security. Nevertheless, it was demonstrated that such an authentication mechanism would need a larger number of samples to enroll the typing characteristics of users. Moreover, these registered characteristics generally undergo aging effects after a time span. Different solutions have been suggested to remedy these variability problems, including template adaptation. In this paper, we propose a double serial adaptation strategy that considers a single-capture-based enrollment process. When using the authentication system, the template of users and the decision/adaptation thresholds are updated. Experimental results on three public keystroke dynamics datasets show the benefits of the proposed method.
机译:网络攻击已遍布世界各地,以窃取诸如商业秘密,知识产权和银行数据之类的信息。面对保存的数据(个人,专业,官员等)不安全的危险,击键动态被提出作为一种有趣的,非侵入性的,廉价的,永久性的且对用户约束不严格的解决方案。根据用户的键入节奏,它提高了逻辑访问的安全性。然而,事实证明,这种身份验证机制将需要大量样本来注册用户的类型特征。此外,这些注册的特性通常会在一段时间后经历老化效果。已经提出了不同的解决方案来补救这些可变性问题,包括模板自适应。在本文中,我们提出了一种双序列适应策略,该策略考虑了基于单捕获的注册过程。使用身份验证系统时,将更新用户模板和决策/适应阈值。在三个公共击键动力学数据集上的实验结果表明了该方法的好处。

著录项

  • 来源
    《Computers & Security》 |2019年第6期|151-166|共16页
  • 作者

  • 作者单位

    ENIT University of Tunis El Manar BP 94 Rommana 1068 Tunis Tunisia Ecole Nationale d'Ingenieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Universite de Sousse 4023 Sousse Tunisie UNICAEN ENSICAEN CNRS GREYC Normandie Univ 14000 Caen France;

    UNICAEN ENSICAEN CNRS GREYC Normandie Univ 14000 Caen France;

    Ecole Nationale d'Ingenieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Universite de Sousse 4023 Sousse Tunisie;

  • 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

    Biometric authentication; Online classification; Template aging; Adaptive strategy; Keystroke dynamics; Template update; Adapted thresholds; KNN-GA;

    机译:生物特征认证在线分类;模板老化;适应性策略;按键动态;模板更新;调整后的阈值;知识网络;

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