TWC: Medium: Collaborative: Long-term Active User Authentication Using Multi-modal Profiles

该项目旨在通过开发生成新的生物特征签名和执行主动和连续的用户认证的有效方法来促进网络安全方面的最新技术。当前的身份验证过程通常在初始登录阶段进行一次，并涉及密码和智能卡等用户代理，这些代理存在几个漏洞。这项研究通过开发概率、生成性模型来表示系统中每个用户的多模式生物识别，从而解决了这些限制，因此任何与用户特定模型的显著偏离都标志着冒名顶替者的存在。这一新技术专门针对伪装攻击的缓解，这些攻击尤其难以检测，因为它们大多由熟悉授权用户活动模式的内部人员执行。该方法能够在入侵者劫持可能暂时离开他/她的控制台的授权个人的用户会话之前识别入侵者。该项目还包括广泛的可用性测试，以在现实生活中的计算机和网络系统中无缝集成身份验证过程，从而确保有关使用网络的人的行为和性能的数据被反馈并纳入未来的安全协议设计。该方法还容易扩展到保护有线和无线网络以及移动设备。

This project aims at advancing the state-of-the-art in cybersecurity by developing efficient methods for generating novel biometric signatures and performing active and continuous user authentication. Current authentication procedures typically occur once at the initial log-in stage and involve user proxies such as passwords and smart cards which suffer from several vulnerabilities. This research addresses these limitations by developing probabilistic, generative models to represent multimodal biometrics of every user in the system, so that any significant deviation from the user-specific model flags the presence of an imposter. This novel technique specifically targets mitigation of masquerading attacks which are particularly challenging to detect as they are mostly carried out by insiders familiar with the activity patterns of the authorized user. The approach enables identification of intruders before they can hijack a user session of an authorized individual who may have momentarily stepped away from his/her console.The project also involves extensive usability tests for seamless integration of the authentication processes in real-life computer and network systems, thus ensuring that data about the behavior and performance of people using the network is fed-back and incorporated into future designs of the security protocols. The methods also readily extend to protecting both wired and wireless networks, and mobile devices.