Ensuring CIA triad for user data using collaborative filtering mechanism

Major online platforms such as Face book, 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. We propose a multicriteria recommendation model that utilizes application-based, user-based, and category-based collaborative filtering mechanisms. Our collaborative filtering mechanisms are based on previous user decisions, and application permission requests to enhance the privacy of the overall site´s user population.