ABSTRACT:

Cloud computing enables customers with limited computational resources to outsource large-scale computational tasks to the cloud, where massive computational power can be easily utilized in a pay-per-use manner. However, security is the major concern that prevents the wide adoption of computation outsourcing in the cloud, especially when end-user's confidential data are processed and produced during the computation. Thus, secure outsourcing mechanisms are in great need to not only protect sensitive information by enabling computations with encrypted data, but also protect customers from malicious behaviors by validating the computation result. Such a mechanism of general secure computation outsourcing was recently shown to be feasible in theory, but to design mechanisms that are practically efficient remains a very challenging problem. Focusing on engineering computing and optimization tasks, this paper investigates secure outsourcing of widely applicable linear programming (LP) computations. In order to achieve practical efficiency, our mechanism design explicitly decomposes the LP computation outsourcing into public LP solvers running on the cloud and private LP parameters owned by the customer. The resulting flexibility allows us to explore appropriate security/efficiency tradeoff via higher-level abstraction of LP computations than the general circuit representation. In particular, by formulating private data owned by the customer for LP problem as a set of matrices and vectors, we are able to develop a set of efficient privacy-preserving problem transformation techniques, which allow customers to transform original LP problem into some random one while protecting sensitive input/output information. To validate the computation result, we further explore the fundamental duality theorem of LP computation and derive the necessary and sufficient conditions that correct result must satisfy. Such result verification mechanism is extremely efficient and incurs close-t- - o-zero additional cost on both cloud server and customers. Extensive security analysis and experiment results show the immediate practicability of our mechanism design.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


MTechProjects.com offering final year NS2 Based Secure Computing MTech Projects, Secure Computing IEEE Projects, IEEE Secure Computing Projects, Secure Computing MS Projects, NS2 Based Secure Computing BTech Projects, Secure Computing
MTechProjects.com offering final year .Net Based Secure Computing MTech Projects, Secure Computing IEEE Projects, IEEE Secure Computing Projects, Secure Computing MS Projects, .Net Based Secure Computing BTech Projects, Secure
MTechProjects.com offering final year Java Based Secure Computing MTech Projects, Secure Computing IEEE Projects, IEEE Secure Computing Projects, Secure Computing MS Projects, Java Based Secure Computing BTech Projects, Secure
PROJECT TITLE :Efficient Secure Outsourcing of Large-Scale Sparse Linear Systems of Equations - 2018ABSTRACT:Solving large-scale sparse linear systems of equations (SLSEs) is one in all the foremost common and basic problems in
PROJECT TITLE :Social-Aware Secret Key Generation for Secure Device-to-Device Communication via Trusted and Non-Trusted Relays - 2018ABSTRACT:Physical layer security (PLS) is a promising technology in device-to-device (D2D)

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry