Research Article
Countering Feedback Sparsity and Manipulation in Reputation Systems
@INPROCEEDINGS{10.1109/COLCOM.2007.4553831, author={Li Xiong and Ling Liu and Mustaque Ahamad}, title={Countering Feedback Sparsity and Manipulation in Reputation Systems}, proceedings={3rd International ICST Conference on Collaborative Computing: Networking, Applications and Worksharin}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2008}, month={6}, keywords={Collaboration Computer science Consumer electronics Control systems Educational institutions Inference algorithms Mathematics Performance evaluation Pollution measurement State feedback}, doi={10.1109/COLCOM.2007.4553831} }- Li Xiong
Ling Liu
Mustaque Ahamad
Year: 2008
Countering Feedback Sparsity and Manipulation in Reputation Systems
COLLABORATECOM
IEEE
DOI: 10.1109/COLCOM.2007.4553831
Abstract
Reputation systems provide a promising way for building trust through social control in collaborative communities by harnessing the community knowledge in the form of feedback. However, reputation systems also introduce vulnerabilities due to potential manipulations by dishonest or malicious players. In this paper, we focus on two closely related problems - feedback sparsity and potential feedback manipulations - and propose a feedback similarity based inference framework. We perform extensive evaluations of various algorithmic components of the framework and evaluate their effectiveness on countering feedback sparsity in the presence of feedback manipulations.
Copyright © 2007–2024 IEEE
