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Erscheinungsjahr: 
2022
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[Journal:] Games [ISSN:] 2073-4336 [Volume:] 13 [Issue:] 4 [Article No.:] 52 [Year:] 2022 [Pages:] 1-11
Verlag: 
MDPI, Basel
Zusammenfassung: 
Nowadays, rating systems play a crucial role in the attraction of customers to different services. However, as it is difficult to detect a fake rating, fraudulent users can potentially unfairly impact the rating's aggregated score. This fraudulent behavior can negatively affect customers and businesses. To improve rating systems, in this paper, we take a novel mechanism-design approach to increase the cost of fake ratings while providing incentives for honest ratings. However, designing such a mechanism is a challenging task, as it is not possible to detect fake ratings since raters might rate a same service differently. Our proposed mechanism RewardRating is inspired by the stock market model in which users can invest in their ratings for services and receive a reward on the basis of future ratings. We leverage the fact that, if a service's rating is affected by a fake rating, then the aggregated rating is biased toward the direction of the fake rating. First, we formally model the problem and discuss budget-balanced and incentive-compatibility specifications. Then, we suggest a profit-sharing scheme to cover the rating system's requirements. Lastly, we analyze the performance of our proposed mechanism.
Schlagwörter: 
fake rating
mechanism design
profit sharing
sybil attack
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