Computing Privacy Risk and Trustworthiness of Users in SNSs

The immense growth of Social Networking Sites (SNSs) has provided fast interactions with strangers, friends and people known in person. This has increase the religious, political and social possibilities for maintaining virtually every type of significant bonds or groups. The personal information used while interacting on social networking sites is an asset for every user profile that may be traded intentionally by a third party for its benefits. Privacy of users is completely based on their awareness of how much of their personal information could be shared without risk. Moreover, users do not give much importance to the privacy risk arising by their information sharing activities. With the rise in different online crimes and malicious behaviors, it is necessary to evaluate the reliability of a profile user. The objective of this paper is to present a method for computing the trust value and privacy risk of users in online social networking sites by integrating basic trust parameters like personal information, recommendations, followings, and customized privacy settings. This will help other users in social network to check whether a person is trustworthy, before accepting him/her in their network. We used real-world data collected from Facebook for calculating and demonstrating the proposed trust model.