Using Private and Public Assessments in Security Information Sharing Agreements

Cost Sharing under Private Valuation and Connection Control

We consider a cost sharing problem on a weighted undirected graph, where all the nodes want to connect to a special node called source, and they need to share the total cost (weights) of the used edges. Each node except for the source has a private valuation of the connection, and it may block others' connections by strategically cutting its adjacent edges to reduce its cost share, which may increase the total cost. We aim to design mechanisms to prevent the nodes from misreporting their valuations and cutting their adjacent edges. We first show that it is impossible for such a mechanism to fu…

私有成本与有向无环图上连接控制下的成本分摊

Cost Sharing under Private Costs and Connection Control on Directed Acyclic Graphs

针对有向无环图上的成本分摊问题，提出一种机制，激励节点提供所有出边且承包商如实报告权重，以最小化总连通成本，并优于两种基准机制。

车载网络中私有数据共享的博弈论框架

Game-Theoretic Framework for Private Data Sharing in Vehicular Networks

提出一种结合Stackelberg博弈的混合架构，通过安全多方计算和激励机制实现隐私保护的车载数据共享，实验验证了其有效性和市场可行性。

大规模频谱共享中的私密真实聚合博弈

Private and Truthful Aggregative Game for Large-Scale Spectrum Sharing

随着信息技术的飞速发展，无线网络的规模越来越大，使得频谱资源比以往任何时候都更加宝贵。为了提高频谱利用效率，博弈论一直被应用于无线网络中频谱共享的研究。然而，现有研究中对无线网络规模的研究相对较少。在本文中，我们介绍了一种新的游戏和模型的频谱共享问题作为一个大规模的，异构的，动态的网络聚合游戏。频谱的大量使用也导致了频谱用户行为的隐私泄露，这就要求在无线网络中保证隐私和真实性。在一个大的分散场景中，每个用户对其他用户的决策没有先验知识，这形成了一个不完全信息博弈。“弱中介”，例如，基站或许可频谱调节器的引入，并把这个游戏变成一个完整的，这是必不可少的，以达到一个纳什均衡（NE）。通过利用以往的信道接入经验，提出了一种在线学习算法，提高了每个用户的效用，实现了随时间的NE。我们的学习算法还为每个用户提供了无遗憾保证。我们的机制承认一个近似的事后NE。我们还证明了它满足联合差分隐私和激励兼容。评估了近似NE的效率，并公开了创新的缩放定律结果。最后，我们提供模拟结果来验证我们的分析。

噪声与私有评估下间接互惠中合作的演化稳定性

Evolutionary stability of cooperation in indirect reciprocity under noisy and private assessment

本文首次从理论上证明间接互惠合作在私有评估下可演化稳定，发现简单常设（SS）规范稳定而严厉评判（SJ）不稳定，揭示适度简单性是维持合作的关键。

Reputation structure in indirect reciprocity under noisy and private assessment

Evaluation relationships are pivotal for maintaining a cooperative society. A formation of the evaluation relationships has been discussed in terms of indirect reciprocity, by modeling dynamics of good or bad reputations among individuals. Recently, a situation that individuals independently evaluate others with errors (i.e., noisy and private reputation) is considered, where the reputation structure (from what proportion of individuals in the population each receives good reputations, defined as goodness here) becomes complex, and thus has been studied mainly with numerical simulations. The p…