An attribute-based access matrix model
Proceedings of the 2005 ACM symposium on Applied computing
Propagation Models for Trust and Distrust in Social Networks
Information Systems Frontiers
Defending against eclipse attacks on overlay networks
Proceedings of the 11th workshop on ACM SIGOPS European workshop
Attribute-Based Access Control with Hidden Policies and Hidden Credentials
IEEE Transactions on Computers
SybilGuard: defending against sybil attacks via social networks
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Inferring binary trust relationships in Web-based social networks
ACM Transactions on Internet Technology (TOIT)
What Anyone Can Know: The Privacy Risks of Social Networking Sites
IEEE Security and Privacy
Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges
IEEE Internet Computing
Trust Inference in Web-Based Social Networks Using Resistive Networks
ICIW '08 Proceedings of the 2008 Third International Conference on Internet and Web Applications and Services
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Collective privacy management in social networks
Proceedings of the 18th international conference on World wide web
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
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With the growth of Social Network Service(SNS), the trust that plays the role of connecting people brings both good user experience and threat. Trust expansion is not only the means by which the SNS users construct their social network , but also exploited by the attackers to collect victims. Hence, it is desirable to find the differences between malicious and normal behaviors. In this paper we analyze the malicious trust expansion behavior and notice that the behavior feature of the malicious users is their weakness. We present the detailed analysis and propose a creative trust control strategy to restrict the malicious users, which fully exploit the characteristic of SNS. The conclusions are positively supported by simulation and experiment in a real SNS scenario.