 Abstract industrial Internet of Things, IOT, is gaining increased attention as a way to achieve greater efficiency and productivity in industry settings. However, there are several challenges associated with data privacy and security when collecting and monitoring data automatically. Traditional authentication methods used in IOT are vulnerable to single-factor authentication, making them less adaptable as the number of users increases or different user categories emerge. To address these issues, this paper proposes a privacy-preserving model for IOT using advanced artificial intelligence techniques. The model consists of two main components, sanitizing and restoring data. Sanitization hides sensitive information while restoring data allows for accurate reconstruction of the original data. A multi-objective optimization problem is formulated to generate optimal keys for sanitization and restoration. The proposed Grasshopper black hole optimization, GBHO, algorithm is used to optimize the objective functions and generate optimal keys. Simulation results show that the proposed model outperforms existing models in terms of various performance metrics. This article was authored by Mohit Kumar, Priya Mukherjee, Sahil Verma, and others. We are article.tv, links in the description below.