ABSTRACT:

Cloud computing permits customers with restricted computational resources to outsource giant-scale computational tasks to the cloud, where massive computational power will be simply utilized in a very pay-per-use manner. However, security is the most important concern that forestalls the wide adoption of computation outsourcing in the cloud, particularly when finish-user's confidential data are processed and produced throughout the computation. Thus, secure outsourcing mechanisms are in nice would like to not only defend sensitive data by enabling computations with encrypted knowledge, however additionally shield customers from malicious behaviors by validating the computation result. Such a mechanism of general secure computation outsourcing was recently shown to be possible in theory, but to design mechanisms that are practically economical remains a terribly difficult drawback. Focusing on engineering computing and optimization tasks, this paper investigates secure outsourcing of widely applicable linear programming (LP) computations. In order to realize practical efficiency, our mechanism design explicitly decomposes the LP computation outsourcing into public LP solvers running on the cloud and non-public 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 have a tendency to can develop a group of economical privacy-preserving downside transformation techniques, that enable customers to remodel original LP problem into some random one while protecting sensitive input/output info. To validate the computation result, we have a tendency to any explore the elemental duality theorem of LP computation and derive the mandatory and sufficient conditions that correct result must satisfy. Such result verification mechanism is extraordinarily economical and incurs close-t- - o-zero extra value on each cloud server and customers. Extensive security analysis and experiment results show the immediate practicability of our mechanism style.


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