Enhancing Security in CNN-Based Travel Recommendation Models Using CKKS Homomorphic Encryption
DOI:
https://doi.org/10.54097/7ay21z97Keywords:
Homomorphic Encryption, Convolutional Neural Networks, Travel Recommendations, Data Security, Privacy PreservationAbstract
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.
References
[1] Boulemtafes, A., Derhab, A., & Challal, Y. (2020). A review of privacy-preserving techniques for deep learning. Neurocomputing, 384, 21-45.
[2] Gilad-Bachrach, R., Dowlin, N., Laine, K., Lauter, K., Naehrig, M., & Wernsing, J. (2016, June). Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy. In International conference on machine learning (pp. 201-210). PMLR.
[3] Akram, A., Khan, F., Tahir, S., Iqbal, A., Shah, S. A., & Baz, A. (2024). Privacy Preserving Inference for Deep Neural Networks: Optimizing Homomorphic Encryption for Efficient and Secure Classification. IEEE Access.
[4] Peijia Zheng, Zhiwei Cai, Huicong Zeng, and Jiwu Huang. 2022. Keyword Spotting in the Homomorphic Encrypted Domain Using Deep Complex-Valued CNN. In Proceedings of the 30th ACM International Conference on Multimedia (MM '22). Association for Computing Machinery, New York, NY, USA, 1474–1483.
[5] N. Jain, K. Nandakumar, N. Ratha, S. Pankanti and U. Kumar, "Optimizing Homomorphic Encryption based Secure Image Analytics," 2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP), Tampere, Finland, 2021, pp. 1-6, doi: 10.1109/MMSP53017.2021.9733620.
[6] Park, J., Kim, D., Kim, J., Kim, S., Jung, W., Cheon, J. H., & Ahn, J. H. (2023). Toward practical privacy-preserving convolutional neural networks exploiting fully homomorphic encryption. arXiv preprint arXiv:2310.16530.I. S. Jacobs and C. P. Bean, “Fine particles, thin films and exchange anisotropy,” in Magnetism, vol. III, G. T. Rado and H. Suhl, Eds. New York: Academic, 1963, pp. 271–350.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.