Behavioural Biometrics for Authentication

该研究项目旨在研究在身份验证场景中使用各种行为生物识别技术的可行性。这一研究领域专注于在人类活动中建立独特的识别模式，如击键、鼠标和触摸屏动态以及语音、步态和认知行为。这通常是一种非侵入性的身份验证方法，因为它不需要用户学习如何操作特定系统或记住唯一的密码和短语。此外，认证不需要任何积极的步骤，而是与系统的正常运作无缝结合。通常，基于行为生物识别的认证系统可以与其他更传统的网络安全措施一起用作多因素保障。尽管这是一个比较好的研究领域，有一些明显成功的项目，但目前使用该技术的成功商业系统很少。这项研究的目标是设计、开发和测试基于行为生物识别的新型身份验证系统，并缩小前景广阔的研究和实际应用之间的差距。例如，开发基于手机使用模式的连续身份验证模型，如触摸屏手势和陀螺仪在太空中的微运动。该项目的另一个方面侧重于查明该领域过去研究中存在的问题以及它往往不适合实际使用的一些原因。例如，一些研究中报告的样本量可能不够大，不足以准确地代表使用这种系统的人群。最后，基于行为生物识别的高精度认证系统的使用带来了独特的隐私挑战。恶意使用这项技术的一种方式是为用户创建唯一的指纹，然后可以利用这些指纹在多个未连接的系统中跟踪行为和身份。还有可能通过用户的行为模式泄露用户的个人信息。性别、年龄和文化群体可以施加上述技术可能检测到的特定特征。该项目属于ESPRC网络安全研究领域。

The research project aims at investigating the feasibility of using various behavioral biometrics in authentication scenarios. This field of study focuses on establishing uniquely identifying patterns in human activity such as keystroke, mouse and touchscreen dynamics as well as voice, gait and cognitive behaviour. This is typically a non-invasive method for authentication as it does not require users to learn how to operate a particular system or remember unique passcodes and phrases. Furthermore, there are no active steps required for authentication but rather it is a seamless integration with the regular operation of the system. Often authentication systems based on behavioural biometrics can be used as a multifactor safeguard in conjunction with other more traditional cybersecurity measures. Despite being a somewhat well research area with some apparently successful projects currently there are few successful commercial systems employing the technology. The goal of the research is to design, develop and test novel systems for authentication based on behavioural biometrics and close the gap between promising research and practical applications. For instance, developing a continuous authentication model based on phone usage patterns such as touchscreen gestures and gyroscope micro movements in space. Another aspect of the project focuses on identifying problems in past research in the area and some of the reasons it tends to be unsuitable for practical use. For example, the reported sample sizes in some of the studies might not be large enough to accurately represent the population using such systems. Finally, there are unique privacy challenges stemming from the use of highly accurate authentication systems based on behavioural biometrics. One way to maliciously employ this technology is to create unique fingerprints for users which can then be exploited for tracking behaviour and identity throughout multiple non-connected systems. It also might be possible to reveal personal information about users through their behaviour patterns. Gender, age and cultural groups could exert specific traits which might be detectable by the technology described above. This project falls within the ESPRC Cybersecurity research area.