Objectives

• Design a system architecture for access, search, and computation of encrypted data in the cloud under a new security threat model.
• Study techniques for efficient access and search of encrypted data in the cloud.
• Study techniques for efficient outsourced computation of encrypted data in the cloud.
• Develop software toolkits and proof of concept demonstrations.
   

Existing Solutions and Their Limitations

• Traditional access control models assume the servers are fully trusted and hence not suitable in heterogeneous computing environments such as the cloud.
• Fully homomorphic encryption (FHE) allows a cloud server to perform computation on encrypted data but with huge overhead.
   

Outcomes/Deliverables

• Mid-term: System design and implementation for access and search of encrypted data in the cloud.
• Final: System design and implementation for secure outsourced computation of encrypted data in the cloud.
   

Practical Applications and Impact

• Secure cloud data storage
• Data localization and access control
• Privacy-preserved machine learning
   

System Architecture/Description

• Cloud service provider is assumed to be honest-but-curious, i.e., provides storage and computation services honestly but is persistently interested in learning users' sensitive information.
• End-to-end data privacy protection for data users.

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