Cloud Computing has great potential of providing robust computational power to the society at reduced cost. It enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner.
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 arbitrary 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-to-zero additional cost on both cloud server and customers. Extensive security analysis and experiment results show the immediate practicability of our mechanism design.
Scope of Work
1. Develope LPP application and solve LPP problems using graphical method.
2. Allow admin to login.
3. Allow admin to View details of the clients.
4. Upload LPP application to the cloud by the admin.
5. Encryption/Decryption while uploading and downloading text file ,images etc from cloud using RSA algorithm.
6. Allow clients to register, login, change password.
7. Provide privilege to access any outsourse in cloud by the client.
8. Client gives the coefficient of LPP equation as input.
9. Generation of LPP result.
10. Allows client to save the result into the file.
Our system accepts few challenges of existing system.
1. LP computations require a substantial amount of computational power and usually involve confidential data; we propose to explicitly decompose the LP computation outsourcing into public LP solvers running on the cloud and private LP parameters owned by the customer. The flexibility of such decomposition allows us to explore higher-level abstraction of LP computations than the general circuit representation for the practical efficiency.
2. It provides security, no one user can see the private LP parameter of other user by providing encryption/decryption technique to the data while passing.
3. It also provides the user to save the contents in their own text file.
4. It provides solution of linear programming application graphically which is easy to understand and help to make economic decisions efficiently.
OBJECTIVE OF SYSTEM
• The main objective of our project is to allow registered users to access the data\application\hardware\software from cloud without installation, configuration, test, secure and update them.
• Users can access on the basis of pay-per-use.
• It can be used for providing hardware and software resources to the customer by simply login to the cloud.
• The users in our project are industries and companies including
&#61607; Airline Industry
&#61607; The Military
&#61607; Capital Budgeting
&#61607; Conservation of resources
&#61607; Economic growth prediction etc.