Research On Efficient Verifiable Data Streaming Protocols In Cloud Environment Environment

Cloud computing offers an economical and convenient way to store massive amounts of data,i.e.users with limited resources and less computing power can continuously outsource local data to cloud servers via lightweight devices such as mobile phones and computers.However,as data is uploaded to the cloud,users will not have direct control and management of this data.At the same time,a large number of cloud data breaches have shown that cloud servers are not entirely trustworthy,and may even tamper with or delete outsourced data for profit and to save resources,or may lose some outsourced data due to the effects of hardware and software-induced downtime failures.Therefore,how to ensure data integrity in a cloud environment remains a challenging technology.In recent years,scholars at home and abroad have conducted a lot of research on the verification of data integrity in cloud environments,and have proposed many specific solutions.For example,schemes such as proof of data ownership,proof of retrievability and verifiable databases enable users to verify that the data returned by the cloud server is consistent with the data initially outsourced and uploaded by the client.However,these approaches are not applicable to data streams with unbounded size and location sensitive characteristics.The emergence of verifiable data streaming(VDS)has addressed the issue of data stream integrity verification.However,existing verifiable data streaming protocols face two problems: firstly,users need sub-linear computational overhead when adding data to a database that contains sensitive private information about the user,but existing protocols do not take privacy protection into account;secondly,for some applications,such as DNA sequence storage in medical systems,historical data needs to be retained for query and research,but existing protocols can only implement operations such as adding,updating and verifying,but not storing and verifying historical data.In order to solve the above problems,this thesis proposes the construction of two chameleon authentication trees,based on which two more efficient verifiable data streaming protocols are designed.The specific work is as follows.1.The existing VDS protocols have the problems of sublinear computational overhead of adding data and no privacy protection.Using a new static chameleon authentication tree structure and AES encryption technology,this thesis proposes an efficient verifiable data streaming protocol with privacy protection.The protocol reduces the computational overhead of adding data,while ensuring the confidentiality of user data using ciphertext transmission.In addition,experimental results show that the protocol achieves efficient data addition and privacy protection while having low storage overhead.Thus,the proposed verifiable data streaming protocol has the advantage of constant computational overhead for adding data and privacy protection.2.To address the problem that existing VDS protocols do not enable querying of updated data and have sub-linear computational overheads when updating data.This thesis proposes a verifiable data streaming protocol that supports update history queries using a novel chameleon authentication tree structure with an update history.The protocol enables data to be added and updated,while allowing multiple updates to a location and retaining each updated version of the data.Furthermore,experimental results show that the protocol not only retains and stores historical versions of data,but also has a low computational overhead when updating data.Thus,the verifiable data streaming protocol proposed in this thesis is efficient in updating data and practical in retaining historical data.