Extending OAuth 2.0 Protocol to Enable Fine Grained Authorization Recommendation Using Multi-criteria Recommendation System

Abstract

Major online platforms such as Facebook, Google, and Twitter allow third -party applications such as games,
and productivity applications access to user online private data. Such accesses must be authorized by users at
installation time. 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, i.e., which access control decisions
are most appropriate. An extension to the OAuth 2.0 authorization enables the provisioning of fine -grained authorization
recommendations to users which grants permissions to third party applications. The system proposes a multicriteria
recommendation model that utilizes application-based, user-based, and category-based collaborative filtering
mechanisms. Proposed System’s collaborative filtering mechanisms are based on previous user decisions, and
application permission requests to enhance the privacy of the overall site’s user population.