Nowadays, rating systems play a crucial role in the attraction of customers for different services. However, as it is difficult to detect a fake rating, attackers can potentially impact the rating's aggregated score unfairly. This malicious behavior can negatively affect users and businesses. To overcome this problem, we take a mechanism-design approach to increase the cost of fake ratings while providing incentives for honest ratings. Our proposed mechanism \textit{RewardRating} is inspired by the stock market model in which users can invest in their ratings for services and receive a reward based on future ratings. 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. Finally, we analyze the performance of our proposed mechanism.
翻译：目前,评级制度在吸引不同服务的客户方面发挥着关键作用,然而,由于很难发现虚假评级,攻击者可能会不公平地影响评级的总分。这种恶意行为可能会对用户和企业产生负面影响。为了解决这一问题,我们采取机制设计办法,增加虚假评级的成本,同时为诚实评级提供奖励。我们提议的机制\ textit{Raydrate}受到股票市场模式的启发,用户可以在其中投资于服务评级,并获得基于未来评级的奖励。首先,我们正式模拟问题,讨论预算平衡和激励兼容性规格。然后,我们建议一种利润分享计划,以满足评级制度的要求。最后,我们分析了拟议机制的业绩。
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