Research On Key Technologies Of Secure Outsourcing In The Cloud

As an important breakthrough in the field of information technology,cloud com-puting can provide on-demand self-service,ubiquitous network access,and flexible and rapid resource management.In recent years,more and more users have chosen to out-source computing and data to cloud platforms.However,this will also cause users to lose control over computing and data,and then lead to many security issues:(1)Cloud platform might has software errors,hardware failures,and external attackes,etc.These will bring the abnormities of outsourcing calculations and storage data;(2)In order to maintain its reputation,the cloud platform will try its best to cover adverse events such as fraudulent outsourcing calculations and storage data loss;(3)For the sake of the economic interests,the cloud platform without assigning resources might deceive its users that it has allocated the corresponding resources.These security issues are the bottlenecks that limit the large-scale deployment of cloud computing.In order to solve these security chanllenges,this dissertation focuses on the key technologies of secure outsourcing under the cloud platform,mainly from the following three aspects:1.Security of outsourcing computation.This issue mainly concerns the privacy of users' outsourced data and the correctness of outsourced computing results.This paper considers outsourcing computation of the large-scale linear matrix equations,which is commonly used in the engineering field.When applying traditional solutions to this problem,the user workload cannot be effectively reduced.In response to this situa-tion,we have proposed a safe and efficient outsourcing computation of the large-scale linear matrix equations:(1)Rapidly realizing the encryption of outsourced problems and the decryption of outsourced computing results through random permutation tech-niques;(2)Efficiently verifying the accuracy of outsourced computing results through the matrix-vector multiplication.The outsourced computing problem of our scheme has the same solution complexity as the original problem,so it will not increase the com-putational load of the cloud platform.Theoretical analysis and simulation experiments show that our solution can take good care of both safety and efficiency.2.Data integrity auditing of outsourcing storage.This problem mainly refers to how users can verify their data integrity without possessing original data.Traditional solutions are often based on a certain security technology to design a data intergrity audting scheme,while ignoring the conversion of other similar security technologies to data intergrity audting schemes.In response to this situation,we propose a transforma-tion method from homomorphic encryption schemes to data integrity auditing schemes:(1)A framework to design data integrity auditing schemes based on homomorphic en-cryption schemes is implemented;(2)Based on the additively,multiplicatively and fully homomorphic encryption schemes,three data integrity auditing schemes are proposed;(3)Data dynamics are supported.Theoretical analysis and simulation experiments show that our general design framework can effectively achieve the conversion from ho-momorphic encryption schemes to data intergrity auditing schemes,and the designed schemes based on homomorphic encryption schemes with low complexity have better performance.3.Third-party data integrity auditing of outsourcing storage.This problem main-ly refers to users outsourcing data auditing work to third-party auditors.Traditional solutions are often based on bilinear pairings,resulting in higher computational com-plexity.In response to this situation,we have proposed a third-party data auditing scheme using the discrete logarithm problem:(1)Data integrity auditing is implement-ed by the third-party auditor;(2)Data outsourcing storage is completed using only basic algebraic operation;(3)Data dynamics are suppoted.Theoretical analysis and simulation experiments show that our solution can efficiently achieve the third-party integrity auditing of cloud storage data.