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Publication# The Role of Game Theory in Key Agreement Over a Public Channel

Abstract

In this work we study the problem of key agreement over a public noiseless channel when Alice, Bob and Charlie observe discrete memoryless sources of an unknown distribution. Alice and Bob want to agree on a key K-AB that is protected from Charlie. At the same time, Alice and Charlie want to agree on a key K-AC that is protected from Bob. In order to construct codebooks for the key agreement, Alice has to know how the sources are distributed. Therefore, she requests Bob and Charlie to send her sufficient information about their observations. We also assume that Bob and Charlie, besides agreeing with Alice on the keys, want to learn as much as possible about the other user's key: we call this quantity the leakage. We model these reports by having Bob and Charlie select discrete memoryless channels and passing their true observations through them. We approach this problem from a game-theoretic point of view. For a class of Bob and Charlie's objective functions which are linear in the key rate and the leakage rate, we characterize a Nash equilibrium. Also, we propose a strategy that Alice can apply in order to ensure that Bob and Charlie's honest reporting is a Nash equilibrium.

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Ontological neighbourhood

Game theory

Game theory is the study of mathematical models of strategic interactions among rational agents. It has applications in all fields of social science, as well as in logic, systems science and computer science. The concepts of game theory are used extensively in economics as well. The traditional methods of game theory addressed two-person zero-sum games, in which each participant's gains or losses are exactly balanced by the losses and gains of other participants.

Normal distribution

In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.

Normal-gamma distribution

In probability theory and statistics, the normal-gamma distribution (or Gaussian-gamma distribution) is a bivariate four-parameter family of continuous probability distributions. It is the conjugate prior of a normal distribution with unknown mean and precision. For a pair of random variables, (X,T), suppose that the conditional distribution of X given T is given by meaning that the conditional distribution is a normal distribution with mean and precision — equivalently, with variance Suppose also that the marginal distribution of T is given by where this means that T has a gamma distribution.

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2021