Multi-Modal Continuous Transparent Biometric Authentication for Mobile Devices

现代移动手持设备能够通过多种网络上的广泛应用提供过多的多媒体服务。这些服务主要是由数据驱动的，这些数据越来越与个人和商业敏感信息联系在一起。全球对拥有50多亿用户的移动设备的依赖程度越来越高，这提高了对终端用户可靠和可靠的核查技术的安全要求，其范围超出了传统的入口点。该项目将分析为移动设备开发一种多模式、连续和透明的认证架构的可行性。拟议的解决方案将使用多种生物识别模式(面部识别、击键分析、行为特征分析)持续和透明地对最终用户进行身份验证，从而大大加强目前最先进的身份验证方法。建议的架构将为最终用户提供一种方便、非侵入性、特定于应用程序的身份验证方法，该方法能够了解各个应用程序的不同风险级别和要求。拟议的架构利用现有的硬件技术，如面部识别、击键分析、应用程序使用和指纹识别，根据最终用户的心理和行为特征不断对其进行身份验证。这一解决方案是可扩展的，并为智能手表物理活动识别等其他身份验证模式提供了进一步的机会。

"The modern mobile handheld device is capable of providing a plethora of multimedia services through a wide range of applications over multiple networks. These services are predominantly driven by data which is increasingly associated with personal and commercially sensitive information. There is an increasing dependence on mobile devices with more than 5 billion users globally and this raises the security requirement for reliable and robust verification techniques of end-users that extends beyond the traditional point-of-entry. This project will analyse the feasibility of developing a multi-modal continuous and transparent authentication architecture for mobile devices. The proposed solution will significantly enhance current state-of-the-art authentication approaches by using multiple biometric modalities (facial recognition, keystroke analysis, behavioural profiling) to continuously and transparently authenticate end-users. The proposed architecture will provide end-users with a convenient, non-intrusive, application specific authentication approach which is capable of understanding the different risk levels and requirements of individual applications. The proposed architecture utilises existing hardware technologies such as facial recognition, keystroke analysis, application usage and fingerprint recognition to continuously authenticate end-users based on their psychological and behavioural characteristics. This solution is scalable and provides further opportunities for additional authentication modalities such as smartwatch physical activity recognition."