A model for calculating user-identity trustworthiness in online transactions

Online transactions require a fundamental relationship between users and resource providers (e.g., retailers, banks, social media networks) built on trust; both users and providers must believe the person or organization they are interacting with is who they say they are. Yet with each passing year, major data breaches and other identity-related cybercrimes become a daily way of life, and existing methods of user identity authentication are lacking. Furthermore, much research on identity trustworthiness focuses on the user's perspective, whereas resource providers receive less attention. Therefore, the current research investigated how providers can increase the likelihood their users' identities are trustworthy. Leveraging concepts from existing research, the user-provider trust relationship is modeled with different transaction contexts and attributes of identity. The model was analyzed for two aspects of user-identity trustworthiness - reliability and authenticity - with a significant set of actual user identities obtained from the U.S. Department of Homeland Security. Overall, this research finds that resource providers can significantly increase confidence in user-identity trustworthiness by simply collecting a limited amount of user-identity attributes.