Abstract
Rating system is a commonly used approach to evaluate a product or service online. It often simply averages the ratings from all users. However, users can manipulate the rating by creating many fake ids to submit non-truthful ratings. In this paper, we propose a weighted rating system underpinned by the connections between users, where the connections can reflect their friendship. Under this rating system, we prove that a user cannot create fake ids to manipulate the evaluation towards her favor. Moreover, the system also represents all ratings, i.e., each single rating will affect the aggregated rating.
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Lian, X., Zhao, D. (2022). A Network-Based Rating Mechanism Against False-Name Attack. In: Long, G., Yu, X., Wang, S. (eds) AI 2021: Advances in Artificial Intelligence. AI 2022. Lecture Notes in Computer Science(), vol 13151. Springer, Cham. https://doi.org/10.1007/978-3-030-97546-3_18
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DOI: https://doi.org/10.1007/978-3-030-97546-3_18
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