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AMBAS: An Autonomous Multimodal Biometric Authentication System

机译：AMBAS：自主多模式生物特征认证系统

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Nowadays, practitioners as well as researchers skilled in the field of Information Technology (IT) attach great importance to the security of IT services. However, the traditional authentication techniques based on single factors such as passwords and tokens suffer from problems related to their robustness. In a recent work, we proposed a new technique called “Multi-factor Authentication based on Multimodal Biometrics (MFA-MB)” to overcome the drawbacks related to these techniques and also the problems related to the biometrics using single traits. Thus, this paper aims to model and develop an Autonomous Multimodal Biometric Authentication System called “AMBAS” using discrete-time Markov chains in order to decrease the complexity of the multimodal biometric system developed and used in the MFA-MB scheme. Eventually, giving the self-control to the AMBAS, offered thus as a new and unique solution, will improve therefore one user experience and achieve as well a good performances in terms of authentication time. This system aims to identify users according to different methodologies, likelihood, last-sate, random and weighting. The system already finds its application in both cloud and mobile computing. While giving a case study with three-modal biometrics, a simulation of different algorithms performed for the four methodologies is done to test the system performances and usefulness.
机译：如今，信息技术（IT）领域的从业者和研究人员非常重视IT服务的安全性。然而，基于诸如密码和令牌之类的单个因素的传统认证技术遭受与其鲁棒性有关的问题。在最近的工作中，我们提出了一种名为“基于多模式生物特征的多因素身份验证（MFA-MB）”的新技术，以克服与这些技术相关的缺点以及与使用单一特征的生物特征相​​关的问题。因此，本文旨在使用离散时间马尔可夫链对称为“ AMBAS”的自主多模式生物特征认证系统进行建模和开发，以降低在MFA-MB方案中开发和使用的多模式生物特征系统的复杂性。最终，将这样的AMBAS自我控制作为一种新的独特解决方案提供，因此将改善一种用户体验，并在身份验证时间方面获得良好的性能。该系统旨在根据不同的方法，可能性，最后状态，随机性和权重来识别用户。该系统已经在云计算和移动计算中找到了应用。在对三模式生物特征进行案例研究的同时，对四种方法执行的不同算法进行了仿真，以测试系统性能和实用性。

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