Preserving User Privacy and Empowering Control in Proximity Marketing.

Based on client location, preferences, and behavior data, proximity marketing has become a potent tool for businesses to interact with their target audience in a personalized way. However, questions regarding user control over personal data and privacy are raised by the use of customer tracking, notably through MAC addresses. We suggest a novel algorithm in this paper to improve user control and privacy protection in proximity marketing systems. Our system uses pseudonymous MAC address switching and a consensus-based methodology to give users more protection and control over their interactions. Through simulations and performance criteria including consensus correctness, convergence, and privacy protection, we assess the algorithm’s efficacy. The outcomes show how the algorithm can enhance user control, protect privacy, reduce the likelihood of tracking and profiling, and guarantee computing efficiency for proximity marketing applications. Our findings provide information for further study and practical use, as well as for the creation of privacy-enhancing proximity marketing tactics.