A novel trust-based access control for social networks using fuzzy systems

Social networks are constantly expanding and attracting more and more users. The users of these networks share plenty of information with their friends, many of which are confidential and private. In this regard, maintaining the security and privacy of users is a major requirement in social networks. Although the traditional access control can help users keep their privacy by applying initial access levels, they are not effective for social networks, considering the dynamic nature of them. Therefore, in this paper, a novel trust-based access control approach has been presented for social network using fuzzy system. The proposed method, SNFTrust, is a combination of trust-based access control and fuzzy inference system which consists of three modules: the user module, the fuzzy trust module, and the access control module. In user module, the user request is analyzed to identify the type of relationships, and the property matrix is created based on user’s activity in social network. In fuzzy trust module, two fuzzy systems are combined to calculate the trust score and to specify the access right. Finally, the access control module enables access to the user account. The proposed approach was implemented using the dataset of a real microblog that attracted over 540 million users on the time we accessed the dataset. The results of experiments indicate that the amount of accuracy is 0.96 and the proposed method has the required flexibility, scalability and accuracy, which can be suitable to apply in various social networks.