scholarly journals Hierarchical remote data possession checking method based on massive cloud files

2016 ◽  
Vol 11 (2) ◽  
pp. 126-134
Author(s):  
Ma Haifeng ◽  
Gao Zhenguo ◽  
Yao Nianmin
Keyword(s):  
Cloud Storage ◽  
False Negative ◽  
False Negative Rate ◽  
Data Integrity ◽  
Communication Overhead ◽  
Local Data ◽  
Cloud Data ◽  
Cloud Storage Service ◽  
Integrity Protection ◽  
Remote Data

Cloud storage service enables users to migrate their data and applications to the cloud, which saves the local data maintenance and brings great convenience to the users. But in cloud storage, the storage servers may not be fully trustworthy. How to verify the integrity of cloud data with lower overhead for users has become an increasingly concerned problem. Many remote data integrity protection methods have been proposed, but these methods authenticated cloud files one by one when verifying multiple files. Therefore, the computation and communication overhead are still high. Aiming at this problem, a hierarchical remote data possession checking (hierarchical-remote data possession checking (H-RDPC)) method is proposed, which can provide efficient and secure remote data integrity protection and can support dynamic data operations. This paper gives the algorithm descriptions, security, and false negative rate analysis of H-RDPC. The security analysis and experimental performance evaluation results show that the proposed H-RDPC is efficient and reliable in verifying massive cloud files, and it has 32–81% improvement in performance compared with RDPC.

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.

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.

Security Analysis on a Public POR Scheme in Cloud Storage

2014 ◽  
Vol 556-562 ◽  
pp. 5395-5399
Author(s):  
Jian Hong Zhang ◽  
Wen Jing Tang
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Security Analysis ◽  
Data Integrity ◽  
Data File ◽  
Cloud Data ◽  
Security Proof ◽  
Cloud Server ◽  
Cloud Data Storage ◽  
Active Attack

Data integrity is one of the biggest concerns with cloud data storage for cloud user. Besides, the cloud user’s constrained computing capabilities make the task of data integrity auditing expensive and even formidable. Recently, a proof-of-retrievability scheme proposed by Yuan et al. has addressed the issue, and security proof of the scheme was provided. Unfortunately, in this work we show that the scheme is insecure. Namely, the cloud server who maliciously modifies the data file can pass the verification, and the client who executes the cloud storage auditing can recover the whole data file through the interactive process. Furthermore, we also show that the protocol is vulnerable to an efficient active attack, which means that the active attacker is able to arbitrarily modify the cloud data without being detected by the auditor in the auditing process. After giving the corresponding attacks to Yuan et al.’s scheme, we suggest a solution to fix the problems.

A New Delegation Provable Data Possession in Public Cloud Storage

2014 ◽  
Vol 644-650 ◽  
pp. 2239-2244
Author(s):  
Bin Li ◽  
Chen Lei Cao ◽  
Jian Yi Liu ◽  
Jin Xia Wei
Keyword(s):  
Performance Analysis ◽  
Cloud Storage ◽  
Security Analysis ◽  
Data Integrity ◽  
Public Cloud ◽  
Provable Data Possession ◽  
Integrity Verification ◽  
And Performance ◽  
Remote Data

Though Cloud storage has developed rapidly in recent years, there still exist some problems obviously. Provable Data Possession (PDP) is proposed to solve the problem of data integrity verification at untrusted cloud stores. This study built a new delegation Provable Data Possession (delegation-PDP), which solves problem when the client has no ability to check its remote data. We study the delegation-PDP and use proxy re-encryption to design it. Then we use the improved Elgamal-based algorithm to implement the scheme. Through security analysis and performance analysis, our protocol is provable secure and efficient.

scholarly journals DDEAS: Distributed Deduplication System with Efficient Access in Cloud Data Storage

2019 ◽  
Vol 9 (2) ◽  
pp. 1943-1949
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Service Providers ◽  
Similar Data ◽  
Data Set ◽  
Cloud Data ◽  
Network Bandwidth ◽  
File Access ◽  
Cloud Storage Service ◽  
Cloud Data Storage

Cloud storage service is one of the vital function of cloud computing that helps cloud users to outsource a massive volume of data without upgrading their devices. However, cloud data storage offered by Cloud Service Providers (CSPs) faces data redundancy problems. The data de-duplication technique aims to eliminate redundant data segments and keeps a single instance of the data set, even if similar data set is owned by any number of users. Since data blocks are distributed among the multiple individual servers, the user needs to download each block of the file before reconstructing the file, which reduces the system efficiency. We propose a server level data recover module in the cloud storage system to improve file access efficiency and reduce network bandwidth utilization time. In the proposed method, erasure coding is used to store blocks in distributed cloud storage and The MD5 (Message Digest 5) is used for data integrity. Executing recover algorithm helps user to directly fetch the file without downloading each block from the cloud servers. The proposed scheme improves the time efficiency of the system and quick access ability to the stored data. Thus consumes less network bandwidth and reduces user processing overhead while data file is downloading.

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