PFI-TT: Behavior-Based Account Recovery, Trust Assessment, and Continuous Authentication for Strengthening Online Identity

该创新-技术翻译合作伙伴关系（PFI-TT）项目的更广泛影响/商业潜力在于为医疗保健、信用卡处理或零售银行业务等不同行业的大量用户检测和预防在线欺诈。 拟议的项目涉及一个新的软件原型的在线欺诈检测和预防的基础上行为的生物识别。 美国消费者每年因账户接管欺诈而损失51亿美元，在线购物是最大的欺诈风险。在电子商务和金融服务等行业，对在线欺诈检测的需求很大。该项目包括团队中研究生的创业教育和领导力发展计划，其中包括客户发现活动，生物识别业务领域经验丰富的企业家的指导，以及识别技术研究中心（CITeR）的创新和创业活动，NSF工业大学合作研究中心（IUCRC）。 扩大参与活动包括支持代表性不足的研究生，并为来自不同群体的本科生提供研究机会。拟议的项目涉及一个新的软件解决方案框架的原型，用于在线欺诈检测和预防，是基于行为生物识别。该软件框架系统地整合了通过账户恢复、通用身份的信任评估和通过登录后身份验证进行检测的预防选项。 该团队还将探索知识产权和用户隐私保护的创新功能/解决方案的设计和实施，两种部署选项，以及额外的登录后身份验证功能，为将行为生物识别和登录后身份验证集成到企业系统中铺平道路。 最后，将探讨可用性考虑因素，包括最终用户在对消费者最重要的安全关键场景中对行为生物识别技术的评估。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is in the online fraud detection and prevention for large populations of users in different industries such as healthcare, credit card processing or retail banking business. The proposed project involves the prototyping of a novel software for online fraud detection and prevention based on behavioral biometrics. US consumers lose $5.1 billion annually due to account takeover fraud and online shopping presents the greatest fraud risk. There is strong demand for online fraud detection in sectors such as e-commerce and financial services. This project includes an entrepreneurial education and leadership development plan for the graduate students in the team, that will include customer discovery activities, mentorship from experienced entrepreneurs in the biometrics business area, and innovation and entrepreneurship activities at the Center for Identification Technology Research (CITeR), a NSF Industry University Collaborative Research Center (IUCRC). Broadening participation activities include supporting underrepresented graduate students and providing research opportunities for undergraduate students from diverse groups. The proposed project involves the prototyping of a novel software solution framework for online fraud detection and prevention that is based on behavioral biometrics. The software framework systematically integrates options for prevention via account recovery, trust assessment of universal identities, and detection via post-login authentication. The team will also explore the design and implementation of innovative features/solutions for intellectual property and user privacy protection, two deployment options, and additional post-login authentication features paving the way for integrating behavioral biometrics and post-login authentication into enterprise systems. Finally, usability considerations including end-user evaluation of behavioral biometrics in security critical scenarios that matter the most to consumers will be explored.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.