Ensuring Dynamic Data Integrity with Public Auditability for Cloud Storage

2012 ◽  
Author(s):  
Long Chen ◽  
Hongbo Chen
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Dynamic Data ◽  
Public Auditability

MB-DDIVR: A Map-Based Dynamic Data Integrity Verification and Recovery Scheme in Cloud Storage

2016 ◽  
pp. 335-345
Author(s):  
Zizhou Sun ◽  
Yahui Yang ◽  
Qingni Shen ◽  
Zhonghai Wu ◽  
Xiaochen Li
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Dynamic Data ◽  
Integrity Verification ◽  
Recovery Scheme

scholarly journals Enabling Decentralized and Dynamic Data Integrity Verification for Secure Cloud Storage via T-Merkle Hash Tree Based Blockchain

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Kai He ◽  
Chunxiao Huang ◽  
Jiaoli Shi ◽  
Xinrong Hu ◽  
Xiying Fan
Keyword(s):  
Cloud Storage ◽  
Large Scale ◽  
Data Integrity ◽  
Third Party ◽  
Prototype System ◽  
Dynamic Data ◽  
Verification Method ◽  
Integrity Verification ◽  
Dynamic Update ◽  
Merkle Hash Tree

Cloud storage provides elastic storage services for enterprises and individuals remotely. However, security problems such as data integrity are becoming a major obstacle. Recently, blockchain-based verification approaches have been extensively studied to get rid of a centralized third-party auditor. Most of these schemes suffer from poor scalability and low search efficiency and even fail to support data dynamic update operations on blockchain, which limits their large-scale and practical applications. In this work, we propose a blockchain-based dynamic data integrity verification scheme for cloud storage with T-Merkle hash tree. A decentralized scheme is proposed to eliminate the restrictions of previous centralized schemes. The data tags are generated by the technique of ZSS short signature and stored on blockchain. An improved verification method is designed to check the integrity of cloud data by transferring computation from a verifier to cloud server and blockchain. Furthermore, a storage structure called T-Merkle hash tree which is built based on T-tree and Merkle hash tree is designed to improve storage utilization of blockchain and support binary search on chain. Moreover, we achieve efficient and secure dynamic update operations on blockchain by an append-only manner. Besides, we extend our scheme to support batch verification to handle massive tasks simultaneously; thus, the efficiency is improved and communication cost is reduced. Finally, we implemented a prototype system based on Hyperledger Fabric to validate our scheme. Security analysis and performance studies show that the proposed scheme is secure and efficient.

scholarly journals Certificateless Dynamic Data Integrity Verification using Lattices in Cloud Storage

2018 ◽  
Vol 11 (10) ◽  
pp. 65-74 ◽  
Author(s):  
Sasikala Chinthakunta ◽  
Shoba Bindu Chigarepalli
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Dynamic Data ◽  
Integrity Verification

MHB*T based dynamic data integrity auditing in cloud storage

2021 ◽  
Author(s):  
Wei Luo ◽  
Wenping Ma ◽  
Juntao Gao
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Dynamic Data

Survey on public auditability to ensure data integrity in cloud storage

2015 ◽  
Vol 37 (3-4) ◽  
pp. 102-110
Author(s):  
Alagumani Selvaraj ◽  
Subashini Sundararajan
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Public Auditability

Data Integrity Techniques in Cloud Computing: An Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 121 ◽  
Author(s):  
Neha Thakur ◽  
Aman Kumar Sharma
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Data Integrity ◽  
Advantages And Disadvantages ◽  
Security Models ◽  
Cloud Storage Service ◽  
Storage Service ◽  
Cloud Users ◽  
It Enterprises

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record.  In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.

Data Integrity Auditing for Secure Cloud Storage using User Behavior Prediction

2021 ◽  
pp. 102245
Author(s):  
Junfeng Tian ◽  
Haoning Wang ◽  
Meng Wang
Keyword(s):  
Cloud Storage ◽  
User Behavior ◽  
Data Integrity ◽  
Behavior Prediction ◽  
Secure Cloud Storage

Data integrity checking with reliable data transfer for secure cloud storage

2018 ◽  
Vol 14 (1) ◽  
pp. 106 ◽  
Author(s):  
Yong Wang ◽  
Xiaoling Tao ◽  
Jianbing Ni ◽  
Yong Yu
Keyword(s):  
Cloud Storage ◽  
Data Transfer ◽  
Data Integrity ◽  
Reliable Data ◽  
Integrity Checking ◽  
Data Integrity Checking ◽  
Secure Cloud Storage ◽  
Reliable Data Transfer

scholarly journals An extensive research survey on data integrity and deduplication towards privacy in cloud storage

2020 ◽  
Vol 10 (2) ◽  
pp. 2011
Author(s):  
Anil Kumar G. ◽  
Shantala C. P.
Keyword(s):  
Cloud Storage ◽  
Data Privacy ◽  
Storage System ◽  
Data Integrity ◽  
Data Deduplication ◽  
Research Issues ◽  
Existing Problems ◽  
Research Survey ◽  
Challenging Tasks ◽  
Future Direction

Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems.

scholarly journals Cloud Data Integrity Verification Algorithm for Sustainable Accounting Informatization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lin Yang
Keyword(s):  
Big Data ◽  
Execution Time ◽  
Cloud Storage ◽  
Computing Time ◽  
Data Integrity ◽  
Cloud Data ◽  
Integrity Verification ◽  
Verification Algorithm ◽  
Advantages And Disadvantages ◽  
Better Than

In recent years, people have paid more and more attention to cloud data. However, because users do not have absolute control over the data stored on the cloud server, it is necessary for the cloud storage server to provide evidence that the data are completely saved to maintain their control over the data. Give users all management rights, users can independently install operating systems and applications and can choose self-service platforms and various remote management tools to manage and control the host according to personal habits. This paper mainly introduces the cloud data integrity verification algorithm of sustainable computing accounting informatization and studies the advantages and disadvantages of the existing data integrity proof mechanism and the new requirements under the cloud storage environment. In this paper, an LBT-based big data integrity proof mechanism is proposed, which introduces a multibranch path tree as the data structure used in the data integrity proof mechanism and proposes a multibranch path structure with rank and data integrity detection algorithm. In this paper, the proposed data integrity verification algorithm and two other integrity verification algorithms are used for simulation experiments. The experimental results show that the proposed scheme is about 10% better than scheme 1 and about 5% better than scheme 2 in computing time of 500 data blocks; in the change of operation data block time, the execution time of scheme 1 and scheme 2 increases with the increase of data blocks. The execution time of the proposed scheme remains unchanged, and the computational cost of the proposed scheme is also better than that of scheme 1 and scheme 2. The scheme in this paper not only can verify the integrity of cloud storage data but also has certain verification advantages, which has a certain significance in the application of big data integrity verification.

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