As cloud computing gains widespread adoption,cloud storage services have become the primary means of data management for users.Authenticated data structures(ADS)are a novel computational model designed to address data...As cloud computing gains widespread adoption,cloud storage services have become the primary means of data management for users.Authenticated data structures(ADS)are a novel computational model designed to address data authentication problems in distributed environments.With the growing demand for robust data security,vulnerability detection in storage systems has become a critical area of focus to ensure resilience against potential threats.However,traditional ADS,while ensuring consistency between cloud data and source data,have limitations in handling dynamic data operations on multiple types of files,storage space expansion,and single-point failure issues.To tackle these issues,this paper proposes a blockchain-assisted classifiable data auditing scheme with dynamic operations.First,trapdoor hash functions are used to construct a binary tree.During dynamic data operations,the impact of hash updates is confined to a subset of nodes,ensuring global stability and reducing computational resource consumption.Second,innovative data structures and verification mechanisms are introduced,reducing the risk of single-point failures by decentralizing the dependency on verification paths.Finally,data types are confirmed based on data identifiers,and corresponding path information is recorded,enabling efficient and rapid dynamic operations on specific types of files within multi-source data.Both security analysis and performance assessment demonstrate that BCDAS conducts data auditing with reliability and efficiency.展开更多
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.90604036)国家杰出青年基金(the National Science Fund of China for Distinguished Young Scholar under Grant No.60525201)国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2007CB807902)
基金Supported by National Key Basic Research Program of China under Grand(2013CB834204)National Natural Science Foundation of China under Grand(61902276)。
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.62302457,62402359)+3 种基金the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F020008)the Fundamental Research Funds of Zhejiang Sci-Tech University(No.22222266-Y)the"Pioneer"and"Leading Goose"R&D Program of Zhejiang(No.2023C01119,2025C02033)。
摘要As cloud computing gains widespread adoption,cloud storage services have become the primary means of data management for users.Authenticated data structures(ADS)are a novel computational model designed to address data authentication problems in distributed environments.With the growing demand for robust data security,vulnerability detection in storage systems has become a critical area of focus to ensure resilience against potential threats.However,traditional ADS,while ensuring consistency between cloud data and source data,have limitations in handling dynamic data operations on multiple types of files,storage space expansion,and single-point failure issues.To tackle these issues,this paper proposes a blockchain-assisted classifiable data auditing scheme with dynamic operations.First,trapdoor hash functions are used to construct a binary tree.During dynamic data operations,the impact of hash updates is confined to a subset of nodes,ensuring global stability and reducing computational resource consumption.Second,innovative data structures and verification mechanisms are introduced,reducing the risk of single-point failures by decentralizing the dependency on verification paths.Finally,data types are confirmed based on data identifiers,and corresponding path information is recorded,enabling efficient and rapid dynamic operations on specific types of files within multi-source data.Both security analysis and performance assessment demonstrate that BCDAS conducts data auditing with reliability and efficiency.