Picking vs. Guessing Secrets: A Game-Theoretic Analysis (Technical Report)

TL;DR

This paper develops a game-theoretic framework to analyze optimal secret selection strategies against strategic adversaries, considering different attack models and revealing conditions under which users can best balance usability and security.

Contribution

It introduces a novel game-theoretic approach to optimize secret choices against strategic adversaries, including analysis of Nash Equilibria, maximin, and Stackelberg strategies.

Findings

Uniform randomization over secret subsets is optimal with limited guesses.

Nash Equilibria may offer no security when attack costs are considered.

Credible commitment is crucial for security when attack costs influence adversary strategies.

Abstract

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.