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Towards Confidential Computing: A Secure Cloud Architecture for Big Data Analytics and AI

Distributed, Parallel, and Cluster Computing 2023-05-30 v1 Artificial Intelligence

Abstract

Cloud computing provisions computer resources at a cost-effective way based on demand. Therefore it has become a viable solution for big data analytics and artificial intelligence which have been widely adopted in various domain science. Data security in certain fields such as biomedical research remains a major concern when moving their workflows to cloud, because cloud environments are generally outsourced which are more exposed to risks. We present a secure cloud architecture and describes how it enables workflow packaging and scheduling while keeping its data, logic and computation secure in transit, in use and at rest.

Keywords

Cite

@article{arxiv.2305.17761,
  title  = {Towards Confidential Computing: A Secure Cloud Architecture for Big Data Analytics and AI},
  author = {Naweiluo Zhou and Florent Dufour and Vinzent Bode and Peter Zinterhof and Nicolay J Hammer and Dieter Kranzlmüller},
  journal= {arXiv preprint arXiv:2305.17761},
  year   = {2023}
}

Comments

2023 IEEE 16th International Conference on Cloud Computing (IEEE CLOUD), Chicago, Illinois, USA, July 2-8, 2023

R2 v1 2026-06-28T10:48:45.416Z