Advancing E-Commerce Security: Strategic Innovations and Future Directions in AI and ML

Abstract

The research carried out in this study aims at analyzing the role that AI as well as ML can play in enhancing the approaches to e-commerce data security. It concentrates to basic AI and ML strategies such as anomaly detection, predictive analysis, and advanced threat detection strategies especially in minimizing cyber risks. This paper also covers privacy preservation, legal issues, and pertinent issues of data quality, interpretability, and scalability. Challenges for the future of e-commerce security are explored as the areas of reinforcement learning, federated learning, and utilizing the block chain as the main directions for the future development in this field. The need to emphasize ethical practice in artificial intelligence is demonstrated for the sustenance of equity and open practices. In conclusion, the research clearly identifies AI and ML as critical strategic assets needed to advance secure e-commerce platforms while building and maintaining customers' trust in today's fast-developing environment.