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Cloud computing enables an economically promising paradigm of computation outsourcing. However, how to protect customers' confidential data processed and generated during the computation is becoming the major security concern. Focusing on engineering computing and optimization tasks, this paper investigates secure outsourcing of widely applicable Linear Programming (LP) computations. The mechanism design explicitly decomposes LP computation outsourcing into public LP solvers running on the cloud and private LP parameters owned by the customer. The resulting flexibility allows one to explore appropriate security/efficiency tradeoff via higher-level abstraction of LP computation than the general circuit representation.
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