Abstract
With the increase of trust recommendation in the network services and applications, a large number of corresponding attacks including white-washing attacks have emerged. This paper proposes a trust optimization model in recommendation system to counter the white-washing attacks. The proposed model first separates the white-washing nodes from other nodes by dividing the nodes into different groups. The grouping will limit the dubious white-washing nodes in the proposed model so as to take these nodes much more cost to become a normal node. Meanwhile, the normal interactions are not affected. Our experimental results show that the proposed model can insulate suspicious white-washing nodes effectively, and ensures the normal interaction activities among normal nodes at the same time. Thus, the proposed model can resist the white-washing attacks effectively.
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Acknowledgement
This work is partly support by the Fundamental Research Funds for the Central Universities(No.NZ2015108), and the China Postdoctoral Science Foundation funded project(2015M571752), and the Jiangsu Planned Projects for Postdoctoral Research Funds (1402033C),and Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China(NO.CAAC-ITRB-201405).
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Wang, Z., Wang, J., Zhao, Y. (2015). The Optimization Model of Trust for White-Washing. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_15
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DOI: https://doi.org/10.1007/978-3-319-27051-7_15
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