Towards Confidential Computing: A Secure Cloud Architecture for Big Data Analytics and AI
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 14 references that are in the map. First posted on arXiv 28 May 2023.
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