Attacker-Defender Signaling Game in Multi-Period Based on Technology Accumulation and Bayesian Learning

摘要

The paper models an incorporated multi-period dynamic signaling game between one attacker and one defender with incomplete information. It is assumed that the defender of two types for high and low attribute properties pays attention to his innovation and development by accumulating technologies, while the attacker can choose to attack or to accumulate technology himself without knowing the defender type. By analogy to perfect Bayesian equilibrium for signaling games, to describe the process that attacker tries to capture useful information from the signals sent by the defender, we give a backward induction algorithm and a numerical example to disclose the equilibrium strategies when to accumulate or to attack in multiple periods by optimizing the payoffs.