ROAuth: recommendation based open authorization

Many major online platforms such as Facebook, Google, and Twitter, provide an open Application Programming Interface which allows third party applications to access user resources. The Open Authorization protocol (OAuth) was introduced as a secure and efficient method for authorizing third party applications without releasing a user's access credentials. However, OAuth implementations don't provide the necessary fine-grained access control, nor any recommendations vis-a-vis which access control decisions are most appropriate. We propose an extension to the OAuth 2.0 authorization that enables the provisioning of fine-grained authorization recommendations to users when granting permissions to third party applications. We propose a mechanism that computes permission ratings based on a multi-criteria recommendation model which utilizes previous user decisions, and application requests to enhance the privacy of the overall site's user population. We implemented our proposed OAuth extension as a browser extension that allows users to easily configure their privacy settings at application installation time, provides recommendations on requested privacy attributes, and collects data regarding user decisions. Experiments on the collected data indicate that the proposed framework efficiently enhanced the user awareness and privacy related to third party application authorizations.