Privacy-Preserving Methods for Outsourced Computation
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If cloud providers are untrusted (for many reasons), outsourcing data intensive computation such as database services and data mining to public clouds raises privacy concerns. The primary purpose of this assignment is to understand the data privacy (confidentiality) problem with outsourced computation in public clouds, and implement several methods to mitigate this problem. This project consists of two parts. (1) Multiplication perturbation methods for outsourced data mining; and (2) Crypto-index for outsourced database services.
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