HEFactory: A symbolic execution compiler for privacy-preserving Deep Learning with Homomorphic Encryption

Author:

Cabrero-Holgueras JoséORCID,Pastrana Sergio

Publisher

Elsevier BV

Subject

Computer Science Applications,Software

Reference28 articles.

1. SoK: Security and privacy in machine learning;Papernot,2018

2. SoK: Privacy-preserving computation techniques for deep learning;Cabrero-Holgueras;Proc Priv Enhanc Technol,2021

3. Crypto-nets: Neural networks over encrypted data;Xie,2014

4. Faster cryptonets: Leveraging sparsity for real-world encrypted inference;Chou,2018

5. How do data science workers collaborate? Roles, workflows, and tools;Zhang;Proc ACM Hum-Comput Interact,2020

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Investigation of Machine Learning Approaches on Security Analysis of Cryptographic Algorithms;Advances in Information Security, Privacy, and Ethics;2024-05-31

2. Privacy-Preserving Network Traffic Analysis Using Homomorphic Encryption;2024 International Conference on Integrated Circuits and Communication Systems (ICICACS);2024-02-23

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