  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.
