Study On Secure Outsourcing Schemes Of Matrix Computing In Cloud Computing Environment

Large-scale problems in the physical and life sciences are being revolutionized by Internet computing technologies that make possible the massive cooperative sharing of computational power, bandwidth, storage, and data. A weak computational device,once connected to such a grid, is no longer limited by its slow speed, small local storage, and limited bandwidth,It can avail itself of the abundance of these resources that are available elsewhere on the network. Cloud computing enables end-users with limited computing resources to outsource large-scale computing problems to the cloud in pay-per-use way, so that large-scale computing power of the cloud can be easily utilized. However, security is still a major issue which hinder outsourcing computing to be widely used, especially when the end user’s confidential data is being processed in the cloud. Two major impediments to the use of computational outsourcing are as follows:(1) the fact that the data in question is often sensitive, e.g., of national security importance, or proprietary and containing commercial secrets, or to be kept private for legal requirements such as the national legislation for health records, or similar laws for patients’ medical records;(2) Answer computed by the cloud server often can not guarantee correct. Therefore, secure outsourcing mechanism need to encrypt the user’s data to protect sensitive information, but also need to check the results from the clouds to protect users from malicious attack behavior. So that no input data will be revealed to a remote server whose computational power is being used, either one’s data or the outcome of the computation on the data. and detecting incorrect answers with high probability.Outsourcing matrix computation has important value in both aspacts of theory and application. Currently research in outsourcing computing is still theoretical. In this paper the existing outsourcing schemes of scientific computation and cryptographic computation are studied. Focusing on the outsourcing problems related to matrix computing. The main researching content of the paper includes the following aspects:(1) A verifiable cloud outsourcing scheme for large matrix determinant computing is proposed. The threshold scheme is based on Shannon diffusion uses unit permutation matrix. Analysis proves the correctness and security of thescheme.Finally according to Python experiment the efficiency of the scheme is being analysed.(2) A secure matrix multiplication outsourcing scheme based on Shannon diffusion is designed, which hide the original matrix in a high-dimensional matrix using unit permutation matrix. In this way privacy of user’s data can be well protected.Meanwhile,we can check whether the server’s returned result is correct in high probability. Finally, as the basic requirements of outsourcing computing model,we analyze and prove that the scheme meets the requirements of correctness,security,and efficiency.(3) Secure multi-clients computation outsourcing model is present. According to the research and analysis of the basic secure outsourcing computation model,a serious problem that the outsourcing model now available hasn’t resolved is pointed out: they can not protect multi-input privacy in outsourcing protocol, multiple clients on the same computing problem have their private input, but they need to protect their data from being informed of the other clients. Therefore,on the basis of secure outsourcing computation model and secure multi-party computation model,the secure multi-party outsourcing computation model is proposed.This model expands the applied scope of general secure outsourcing computing model. And further, function definition, formal definition and solving method is given. After that, a secure multi-matrix summation outsourcing scheme based on Shamir secret sharing is designed. At last,analysis proves the therehold scheme meet the requirements of correctness, security, and efficiency.