Research On Outsourced Data Self-auditing Based On Blockchain

The rapid development of Cloud Computing and the Internet of Things has led to the explosive growth of data.More and more users outsource data to cloud service providers to reduce the costs of data storage and management.However,the management and ownership of data will be separated in the cloud environment,which will threaten the outsourced data.Concretely,the cloud may damage the users’ data due to hardware and software failures or human errors.Besides,users who never store the outsourced data locally cannot directly verify the integrity of data.Therefore,how to ensure the integrity of outsourced data has become a research hotspot in the field of data security.The integrity auditing schemes for outsourced data are proposed to solve the above problem.Existing auditing schemes can verify the integrity of outsourced data without retrieving the entire data.These schemes will introduce a centralized TPA to replace users for integrity audits.As the centralized architecture,TPA vulnerably suffers single-point-of-failure or colludes with cloud servers to deceive users.The emergence of blockchain can be well solved the problem of TPA by deploying audit tasks on smart contracts.However,smart contracts can only support simple cryptographic primitives,and blockchain-based auditing schemes are inefficient and non-scalable.Furthermore,it is also challenging work to improve the computational and storage overhead for the users and storage providers.This thesis will focus on the efficient audit scheme in the blockchain to solve the above problems.The main contributions are as follows:(1)This thesis proposes a blockchain-based self-auditing scheme for outsourced data under the decentralized storage environment.Storage providers utilize the blockchain information to generate the challenged set and interact with the blockchain to complete the audit tasks to achieve self-auditing.Therefore,we remove TPA from the traditional scheme and never need users online to challenge storage nodes.Besides,we reduce the computational overhead and the storage redundancy of audit authenticators by utilizing the Pedersen-based polynomial commitment scheme,which can commit two polynomials simultaneously.Finally,we evaluated on-chain consumption in the Ethereum test network.Compared with existing blockchain-based auditing schemes,our scheme reduces the computational overhead on the blockchain.(2)Furthermore,this thesis proposes a blockchain-based self-auditing scheme with batch verification and fault localization.We design a batch verification algorithm to improve the computational cost of multiple proofs based on the batch opening polynomial commitment scheme.Secondly,our scheme proposes a fault localization algorithm based on the Rev-tree technology,which improves the computational cost to find the fault proofs after the batch verification algorithm fails.Finally,we optimize the interaction process between storage nodes and the blockchain to improve the communication overhead.Evaluation shows the scheme is efficient.