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Ecologically Inspired Framework for Assured Data Cloud
As a part of this project, we explored risk based approaches for securely managing data in the cloud. Basically, inspired by how living organisms manage risks in nature while preserving and conserving energy, we developed novel risk based approaches that balances risk (i.e., potential sensitive data disclosure risk), computational cost (i.e., how long will it take to run the security enhanced tasks in the cloud?), monetary cost (i.e., how much more you would pay to the cloud service provider due to security enhanced cloud computing?). In different settings, we solve the variants of the multi-objective optimization framework where we find best query execution plan Q among all possible query plans that minimizes the total run time while it does not exceed the predefined monetary costs and risk measures.
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