Verification of data redundancy in cloud storage

Author(s):  
Zhan Wang ◽  
Kun Sun ◽  
Jiwu Jing ◽  
Sushil Jajodia
2011 ◽  
Vol 55 (5) ◽  
pp. 1100-1113 ◽  
Author(s):  
Lluis Pamies-Juarez ◽  
Pedro García-López ◽  
Marc Sánchez-Artigas ◽  
Blas Herrera

Author(s):  
Shynu P. G. ◽  
Nadesh R. K. ◽  
Varun G. Menon ◽  
Venu P. ◽  
Mahdi Abbasi ◽  
...  

AbstractData redundancy is a significant issue that wastes plenty of storage space in the cloud-fog storage integrated environments. Most of the current techniques, which mainly center around the static scenes, for example, the backup and archive systems, are not appropriate because of the dynamic nature of data in the cloud or integrated cloud environments. This problem can be effectively reduced and successfully managed by data deduplication techniques, eliminating duplicate data in cloud storage systems. Implementation of data deduplication (DD) over encrypted data is always a significant challenge in an integrated cloud-fog storage and computing environment to optimize the storage efficiently in a highly secured manner. This paper develops a new method using Convergent and Modified Elliptic Curve Cryptography (MECC) algorithms over the cloud and fog environment to construct secure deduplication systems. The proposed method focuses on the two most important goals of such systems. On one side, the redundancy of data needs to be reduced to its minimum, and on the other hand, a robust encryption approach must be developed to ensure the security of the data. The proposed technique is well suited for operations such as uploading new files by a user to the fog or cloud storage. The file is first encrypted using the Convergent Encryption (CE) technique and then re-encrypted using the Modified Elliptic Curve Cryptography (MECC) algorithm. The proposed method can recognize data redundancy at the block level, reducing the redundancy of data more effectively. Testing results show that the proposed approach can outperform a few state-of-the-art methods of computational efficiency and security levels.


2015 ◽  
Vol 81 ◽  
pp. 164-177 ◽  
Author(s):  
Zhen Huang ◽  
Jinbang Chen ◽  
Yisong Lin ◽  
Pengfei You ◽  
Yuxing Peng

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Tingting Yu

In order to meet the requirements of users in terms of speed, capacity, storage efficiency, and security, with the goal of improving data redundancy and reducing data storage space, an unbalanced big data compatible cloud storage method based on redundancy elimination technology is proposed. A new big data acquisition platform is designed based on Hadoop and NoSQL technologies. Through this platform, efficient unbalanced data acquisition is realized. The collected data are classified and processed by classifier. The classified unbalanced big data are compressed by Huffman algorithm, and the data security is improved by data encryption. Based on the data processing results, the big data redundancy processing is carried out by using the data deduplication algorithm. The cloud platform is designed to store redundant data in the cloud. The results show that the method in this paper has high data deduplication rate and data deduplication speed rate and low data storage space and effectively reduces the burden of data storage.


Author(s):  
Wan Nurazieelin Wan Abd Manan ◽  
Mohamad Aizi Salamat

<span>Reduction of dynamic data redundancy in cloud computing is one of the best ways to maintain the storage capacity from being fully utilized. Cloud storage is a part of cloud computing technology which holds a high demand in any organization for reducing the cost of purchasing and maintaining storage infrastructures. Increase in the number of users will require a larger storage capacity for storing their data. Reduction of dynamic data redundancy allows service providers to be energy savvy and minimize maintenance cost. Recent researches focus more on static data nature despite its limited capability as compared to dynamic data characteristic in cloud storage. Therefore, this paper theoretically compares various techniques for reduction of redundant dynamic data in cloud computing and suggests the best technique for completing the task in terms of response time.</span>


2012 ◽  
Vol 3 (3) ◽  
pp. 60-61
Author(s):  
V.Sajeev V.Sajeev ◽  
◽  
R.Gowthamani R.Gowthamani

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Irfan Santiko ◽  
Rahman Rosidi ◽  
Seta Agung Wibawa

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