E-commerce consumer privacy protection and immersive business experience simulation based on intrusion detection algorithms

Abstract

In the process of e-commerce shopping, immersive service experiences and entertainment shopping models are increasingly popular among consumers. This article analyzes the privacy protection and immersive business experience simulation of e-commerce consumers based on intrusion detection algorithms.After studying intrusion detection algorithms, this article delves into personal privacy protection models related to public network e-commerce consumption. This article first explores the significance and current status of intrusion detection algorithms, as well as the research status of deep learning in this field, and conducts comparative experiments on improved intrusion detection algorithms. Then, after analyzing the requirements of the evaluation support system for privacy protection algorithms, the overall framework of the personal privacy protection system was designed and studied. Intrusion detection algorithm identifies possible privacy threats by monitoring and analyzing user behavior data, and then proposes an immersive business experience simulation framework, which includes virtual reality technology and personalized recommendation system, enabling users to immerse themselves in the virtual environment of e-commerce platform and enjoy personalized shopping experience. Interactive experiences can provide e-commerce consumers with more shopping pleasure, and at the same time, businesses need to ensure that consumer privacy is effectively protected during the consumption process. In the end, a new personal privacy protection model was successfully constructed, which verified the great advantages of the algorithm in terms of running time, and concluded that using intrusion detection algorithms can greatly protect the personal privacy of e-commerce consumers using public networks.