Confidential and Verifiable Machine Learning Delegations on the Cloud

ePrint Report: Confidential and Verifiable Machine Learning Delegations on the Cloud

Wenxuan Wu, Soamar Homsi, Yupeng Zhang

With the growing adoption of cloud computing, the ability to store data and delegate computations to powerful and affordable cloud servers have become advantageous for both companies and individual users. However, the security of cloud computing has emerged as a significant concern. Particularly, Cloud Service Providers (CSPs) cannot assure data confidentiality and computations integrity in mission-critical applications. In this paper, we propose a …

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