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Picking vs. Guessing Secrets: A Game-Theoretic Analysis

机译:选择与猜测秘密:博弈论分析

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Choosing a hard-to-guess secret is a prerequisite in many security applications. Whether it is a password for user authentication or a secret key for a cryptographic primitive, picking it requires the user to trade-off usability costs with resistance against an adversary: a simple password is easier to remember but is also easier to guess, likewise, a shorter cryptographic key may require fewer computational and storage resources but it is also easier to attack. A fundamental question is how one can optimally resolve this trade-off. A big challenge is the fact that an adversary can also utilize the knowledge of such usability vs. security trade-offs to strengthen its attack. In this paper, we propose a game-theoretic framework for analyzing the optimal trade-offs in the face of strategic adversaries. We consider two types of adversaries: those limited in their number of tries, and those that are ruled by the cost of making individual guesses. For each type, we derive the mutually-optimal decisions as Nash Equilibria, the strategically pessimistic decisions as maximin, and optimal commitments as Strong Stackelberg Equilibria of the game. We establish that when the adversaries are faced with a capped number of guesses, the user's optimal trade-off is a uniform randomization over a subset of the secret domain. On the other hand, when the attacker strategy is ruled by the cost of making individual guesses, Nash Equilibria may completely fail to provide the user with any level of security, signifying the crucial role of credible commitment for such cases. We illustrate our results using numerical examples based on real-world samples and discuss some policy implications of our work.
机译:选择难以猜测的秘密是许多安全应用程序中的先决条件。无论是用于用户身份验证的密码还是用于加密基元的秘密密钥,选择该密码都需要用户权衡可用性成本和抵抗对手的能力:简单的密码更容易记住,但也更容易猜测,同样,较短的加密密钥可能需要较少的计算和存储资源,但也更容易受到攻击。一个基本的问题是,如何才能最佳地解决这一折衷问题。一个巨大的挑战是,攻击者还可以利用这种可用性与安全性权衡的知识来增强其攻击能力。在本文中,我们提出了一个博弈论框架来分析面对战略对手时的最佳权衡。我们考虑两种类型的对手:尝试次数有限的对手,以及受个人猜测成本影响的对手。对于每种类型,我们将相互最优的决策推导出为Nash均衡,将战略上悲观的决策推导为最大化,将最优承诺推定为博弈的Strong Stackelberg均衡。我们确定,当对手面临最多的猜测数时,用户的最佳权衡是在秘密域的一个子集上进行统一的随机分配。另一方面,当攻击者的策略受到进行单个猜测的代价的支配时​​,Nash Equilibria可能完全无法为用户提供任何级别的安全性,这表明在这种情况下可信承诺的关键作用。我们使用基于实际样本的数值示例来说明我们的结果,并讨论我们工作的一些政策含义。

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