14-01-2013, 04:54 PM
Secure and Practical Outsourcing of Linear Programming in Cloud Computing
1Secure and Practical.ppt (Size: 282 KB / Downloads: 60)
Introduction
Linear Programming (LP)
Widely used
Analyze and optimize real-world systems
Require large computing power
Usually involve confidential data
Business financial records, proprietary research data, etc.
Secure outsourcing
Input/output privacy
Cheating resilience
Existing System
We first formulate private data owned by the customer for LP problem as a set of matrices and vectors.
This higher level representation allows us to apply a set of efficient privacy-preserving problem transformation techniques, including matrix multiplication and affine mapping, to transform the original LP problem into some arbitrary one while protecting the sensitive input/output information.
Proposed System
This section presents our LP outsourcing scheme which provides a complete outsourcing solution for – not only the privacy protection of problem input/output, but also its efficient result checking.
We start from an overview of secure LP outsourcing design framework and discuss a few basic techniques and their demerits, which leads to a stronger problem transformation design utilizing mapping.
We then discuss effective result verification by leveraging the duality property of LP.