Enhancing Security in CNN-Based Travel Recommendation Models Using CKKS Homomorphic Encryption
Tianhao Chen · Journal of Computing and Electronic Information Management · 2024
This study explores the integration of CKKS homomorphic encryption with convolutional neural networks (CNNs) to enhance the security of travel recommendation systems. By adapting CNN architectures to operate efficiently on encrypted data using CKKS, we address the challenge of maintaining the users’ privacy without compromising system performance. Key results indicate significant improvements in data security with minimal impact on recommendation accuracy.