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Secure Optimization Computation Outsourcing in Cloud Computing: A Case Study of Linear Programming
  • Secure Optimization Computation Outsourcing in Cloud Computing: A Case Study of Linear Programming

Secure Optimization Computation Outsourcing in Cloud Computing: A Case Study of Linear Programming

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Secure Optimization Computation Outsourcing in Cloud Computing: A Case Study of Linear Programming

Cloud computing provides paradigm of computation outsourcing. During the computation, protection of customer’s confidential generated and processed data is becoming the major security concern. Focusing on engineering computing and optimization tasks, the proposed system investigates secure outsourcing of widely applicable linear programming (LP) computations.

Proposed 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 the user to explore appropriate security/efficiency tradeoff via higher-level abstraction of LP computation than the general circuit representation.

The protection of sensitive input/output information is done by formulating and developing a private LP problem as a set of matrices/vectors, efficient privacy-preserving problem transformation techniques, which allow customers to transform the original LP into some random one.Secure Optimization Computation Outsourcing in Cloud Computing.

To validate the computation result, we further explore the fundamental duality theorem of LP and derive the necessary and sufficient conditions that correct results must satisfy. Such result verification mechanism is very efficient and incurs close-to-zero additional cost on both cloud server and customers.

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