Collaborative Regulation of the “Personalization-Privacy” Dilemma Based on Stochastic Catastrophe Theory

The frequent occurrence of privacy - risk events such as “APP eavesdropping”, “excessive data collection”, and “big data price discrimination” has made the “personalization - privacy” dilemma that users face in precision marketing increasingly severe. There is an urgent need for collaborative regulation by enterprises and the government. However, there are many uncertain factors in the complex external environment, which can easily trigger mutations in the collaborative regulation involving multiple participants. This paper expands the evolutionary game model using random interference and stochastic dynamics equations. Based on catastrophe theory, the stochastic dynamics equations are transformed into a catastrophe model through the limiting probability density to study the nonlinear evolution process of collaborative regulation and reveal the mutation control strategies for collaborative regulation. This research provides new insights into the internal mutation mechanism of collaborative regulation evolution, offering a new way to solve the “personalization - privacy” dilemma of users in precision marketing.