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arXiv 2310.09232cs.ITmath.IT
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猜测数界限与结合信息论方法的秘密共享

Bounds on Guessing Numbers and Secret Sharing Combining Information Theory Methods

Emirhan Gürpınar

AI总结:

本文开发了结合非经典香农熵不等式的计算机辅助证明方法,应用于秘密共享和帽子猜测游戏,通过线性规划和对称性改进下界和上界。

摘要:

本文致力于开发一些计算机辅助证明方法,这些方法涉及香农熵的非经典不等式。研究了信息不等式的两个应用领域:秘密共享方案和帽子猜测游戏。在前者中,一个随机秘密值被转换为分发给若干参与者的份额,使得只有合格的参与者组才能恢复该秘密值。在后者中,每个参与者被分配一种帽子颜色,他们试图猜测自己的颜色,同时只能看到其他一些人的颜色。目标是最大化每个玩家都猜对的概率,最优概率取决于底层的有向图。我们针对这两个问题使用了非香农型信息不等式的方法,该方法可追溯到Z. Zhang和R. W. Yeung的工作。我们采用了线性规划技术,该技术允许间接应用新的信息不等式,甚至无需显式写出它们。为了降低所涉及的线性规划问题的复杂度,我们广泛使用了对称性考虑。利用这些工具,我们改进了前者问题中密钥大小与秘密大小之比的下降界,以及后者问题中与Riis提出的一个开放问题相关的十个顶点图之一的上界。

英文摘要:

This paper is on developing some computer-assisted proof methods involving non-classical inequalities for Shannon entropy. Two areas of the applications of information inequalities are studied: Secret sharing schemes and hat guessing games. In the former a random secret value is transformed into shares distributed among several participants in such a way that only the qualified groups of participants can recover the secret value. In the latter each participant is assigned a hat colour and they try to guess theirs while seeing only some of the others'. The aim is to maximize the probability that every player guesses correctly, the optimal probability depends on the underlying sight graph. We use for both problems the method of non-Shannon-type information inequalities going back to Z. Zhang and R. W. Yeung. We employ the linear programming technique that allows to apply new information inequalities indirectly, without even writing them down explicitly. To reduce the complexity of the problems of linear programming involved in the bounds we extensively use symmetry considerations. Using these tools, we improve lower bounds on the ratio of key size to secret size for the former problem and an upper bound for one of the ten vertex graphs related to an open question by Riis for the latter problem.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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