Trustworthy Approach for Online Social Networks using Data mining (Journal of Basic and Applied Research in Biomedicine, 2022)
Online Social Networks is an active & important research area in the recent years. It is a platform to build social relations among people who share similar interests, activities, backgrounds or real-life connections. Social interactions among users are constructed basically on the trust. Social trust implies that users behave according to the expectation of other users, are trustworthy and expect trust from other users. As two users interact with each other frequently, their relationship strengthens & trust evolves based on their experience. The objective of the project is to develop a secure social networking with decision support system to identify trustworthy friends. We need to identify trustworthy people in order to protect user’s important information from being misused. We define trust relationships by how much we trust the content posted or broadcasted by our friends. Depending on the past user interactions and profile similarity, we measure the trust values. Trust values are maintained by user & are calculated according to their own experiences & information from social relationships contacts. In this project, we can find trustworthy friends based on ratings review, based on which user can make decisions & provide access permissions to trustworthy users only.