Enhancing E-commerce Recommendation Systems Through Advanced Encryption Techniques
Shithan Ghosh, Sanjukta Mondal, Arnab Laha, Bishakha Mondal, Atri Bandyopadhyay, Prasun Chakraborty · 2024
In the domain of e-commerce recommendation systems, our research introduces an innovative strategy by incorporating secure encryption techniques. This approach aims to protect user privacy and data security while enhancing recommendation accuracy. We strive to find a delicate balance between ensuring data protection and delivering personalized user experiences in the e-commerce sphere. Through rigorous experimentation and thorough analysis, we assess how different encryption methods impact system performance, providing valuable insights for both industry practitioners and researchers. Our study not only illuminates the complex interplay between security measures and system efficiency but also serves as a foundation for advancing secure recommender systems, enabling stakeholders to navigate the intricacies of ecommerce while maintaining the utmost standards of user privacy and data security.