Dynamic game-theoretic modeling of strategic fake data under competitive and technological asymmetry

The strategic dissemination of fake data presents a significant challenge in data-driven decision-making, yet existing studies often overlook the complex dynamics introduced by a competitor to the information sender. This paper addresses this gap by developing a dynamic game-theoretic model involving a data receiver, a primary sender who may strategically distort information, and a competing information source. Employing the framework of Markov Perfect Equilibrium, we derive the optimal dynamic strategies for all involved agents. Specifically, we investigate how the receiver navigates data uncertainty to minimize economic losses, while the primary sender seeks to maximize payoff through strategic data dissemination dynamically responding to the competitor’s actions. Furthermore, we investigate the impact of differing technological effectiveness — especially in data generation and obfuscation — of both the primary sender and the competitor on equilibrium outcomes and system dynamics. Our findings demonstrate that strategic manipulation combined with technological asymmetry can induce complex, potentially nonlinear behaviors within information systems. These findings provide a robust theoretical foundation for understanding behavior in contested information environments and provide practical insights for organizations seeking to mitigate economic losses and evaluate risks associated with data manipulation.