M.A. Thesis:

ARole-Based Access Control Model Based on Dynamic Trust

With the rapid development of computer networks, the issue of security in networks has become more important. Social networks and multi-agent systems and peer-to-peer networks are intrinsically open and highly dynamic. That is why the behavior of entities in them is not clear. And this has made networks vulnerable to threats and attacks. That's why users were forced to restrict their online and online sharing of online content that has been blocking the potential use of social networks or Internet networks. Social networking users are always struggling to create the right way to create a secure environment without worrying about the exchange of information in these networks. In this thesis, we focus on enhancing the security of the evaluation of the trust of entities and identifying malicious and well-known malicious users for better interaction and ultimately assigning a role to them. Given the level of trust or, in other words, trust management among entities, one aspect that needs to be considered in trust management systems is the time and dynamics of trust. So far, researchers have come up with many ways to calculate the amount of trust in users on social networks and try to improve the accuracy of the assessment of trust. In this thesis, we tried to increase the reliability of the trust assessment and reduce the absolute magnitude of the error by presenting a weighted slider window based confidence estimation model. In this model, considering the time parameter and the issue of trust dynamics, we try to reduce the impact of old interactions in order to improve the accuracy of trust assessment. By simulating and comparing its results, it has been shown that the accuracy of trust in this method is in Comparison with the proposed method is improved.

Keywords: social networks, access control, trust assessment, weighted slider window, trust dynamics