scholarly journals STRENGTHNING THE PRODUCTIVITY OF STORAGE FOR BIG DATA STORAGE SYSTEMS USING DISTRIBUTED DEDUPLICATION

2020 ◽  
pp. 691-694
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Similar Data ◽  
Data Deduplication ◽  
Data Set ◽  
Recovery Algorithm ◽  
Network Bandwidth ◽  
File Access

Cloud storage is one of the key features of cloud computing, which helps cloud users outsource large numbers of data without upgrading their devices. However, Cloud Service Providers (CSPs) data storage faces problems with data redundancy. The data deduplication technique aims at eliminating redundant information segments and maintains one single instance of the data set, even if any number of users own similar data set. Since blocks of data are spread on many servers, each block of the file has to be downloaded before restoring the file to decrease system output. We suggest a cloud storage server data recovery module to improve file access efficiency and reduce time spent on network bandwidth. Device coding is used in the suggested method to store blocks in distributed cloud storage, and for data integrity, MD5 (Message Digest 5) is used. Running recovery algorithm helps the user to retrieve a file directly from the cloud servers without downloading every block. The scheme proposed improves system time efficiency and the ability to access the stored data quickly. This reduces bandwidth consumption and reduces overhead user processing while downloading the data file.

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.

scholarly journals Deduplication in Cloud Storage

2019 ◽  
Vol 9 (2S) ◽  
pp. 364-368
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Cloud Service ◽  
Information Storage ◽  
Cloud Environment ◽  
Data Deduplication ◽  
Cloud Service Provider ◽  
Level Data ◽  
Block Level ◽  
Individual Client

Cloud Computing is well known today on account of enormous measure of data storage and quick access of information over the system. It gives an individual client boundless extra space, accessibility and openness of information whenever at anyplace. Cloud service provider can boost information storage by incorporating data deduplication into cloud storage, despite the fact that information deduplication removes excess information and reproduced information happens in cloud environment. This paper presents a literature survey alongside different deduplication procedures that have been based on cloud information storage. To all the more likely guarantee secure deduplication in cloud, this paper examines file level data deduplication and block level data deduplication.

scholarly journals Federated Cloud Storage Management Through Provable Data Possession using Dynamic Audit Protocol

2019 ◽  
Vol 8 (2S3) ◽  
pp. 662-665
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Application Programming Interface ◽  
Third Party ◽  
Web Browser ◽  
Free Data ◽  
Cloud Service Providers ◽  
Storage Area

Cloud computing is a technology for sharing the resources for on demand request and for processing the data. It facilitates cloud storage for adopting cloud users with the help of cloud service providers. It enhances need of enterprises by adhering large volume of data to store and owned privately through third party auditors via data centres. The proposed system analyse cloud storage and provide free data storage for computing the data and maintain variety of cloud storage in one place. This scenario promotes storage of files in one system, so the user doesn’t require various accounts like GoogleDrive, Microsoft Onedrive and Dropbox. This application enhances multiple cloud storage for accessing all files in one particular storage area. The proposed system eradicates visiting of multiple sites for downloading the apps and reduces installing of multiple apps for downloading all the files. The work mainly focuses on the SaaS that permits users to upload data and share the resources from the cloud to post in the Web browser. Our work designed for creating single level of Application programming interface which is for all the cloud service providers. This adopts external applications that leverage the service of platform which is easier to build scalable, and automated cloud based applications. The final API promotes multiple cloud storage in one place and leads to provision Federated Cloud

scholarly journals Data Storage and Retrieval with Deduplication in Secured Cloud Storage

2019 ◽  
Vol 9 (1) ◽  
pp. 609-615
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Modern Technology ◽  
Current Data ◽  
Data Deduplication ◽  
Data Accessibility ◽  
Storage And Retrieval ◽  
Network Bandwidth ◽  
Secured Data ◽  
Client Side

The Cloud Storage can be depicted as a service model where raw or processed data is stored, handled, and backed-up remotely while accessible to multiple users simultaneously over a network. Few of the ideal features of cloud storage is reliability, easy deployment, disaster recovery, security for data, accessibility and on top of that lesser overall storage costs which removes the hindrance of purchasing and maintaining the technologies for cloud storage. In this modern technology world, massive amount of data are produced in day to day life. So, it has become necessary to handle those big data on demand which is a challenging task for current data storage systems. The process of eliminating redundant copies of data thereby reducing the storage overhead is termed as Data Deduplication (DD). One of the ultimate aim of this research is to achieve ideal deduplication on secured data of client side. On the other hand as the client’s data are encrypted with different keys, the cross user deduplication is merely impossible as having a single key encryption among multiple user’s leads to an in secure system resulting in fragile to client’s expectations. The proposed research adapts Message Locked Encryption (MLE) technique that looks for redundant files in cloud before uploading the client’s file which eventually reduces the storage. Since the redundant files are swept, the network bandwidth is considerably reduced with respect to the redundant contents uploaded several times.

scholarly journals Secure Data Deduplication in Cloud Environments

2021 ◽  
Author(s):  
Fatema Rashid
Keyword(s):  
Video Processing ◽  
Service Providers ◽  
Cloud Service ◽  
Error Correcting Codes ◽  
Digital Data ◽  
Data Deduplication ◽  
Data Types ◽  
Efficient Manner ◽  
Secure Data ◽  
Cloud Environments

With the tremendous growth of available digital data, the use of Cloud Service Providers (CSPs) are gaining more popularity, since these types of services promise to provide convenient and efficient storage services to end-users by taking advantage of a new set of benefits and savings offered by cloud technologies in terms of computational, storage, bandwidth, and transmission costs. In order to achieve savings in storage, CSPs often employ data dedplication techniques to eliminate duplicated data. However, benefits gained through these techniques have to balanced against users' privacy concerns, as these techniques typically require full access to data. In this thesis, we propose solutions for different data types (text, image and video) for secure data deduplication in cloud environments. Our schemes allow users to upload their data in a secure and efficient manner such that neither a semi-honest CSP nor a malicious user can access or compromise the security of the data. We use different image and video processing techniques, such as data compression, in order to further improve the efficiency of our proposed schemes. The security of the deduplication schemes is provided by applying suitable encryption schemes and error correcting codes. Moreover, we propose proof of storage protocols including Proof of Retrievability (POR) and Proof of Ownership (POW) so that users of cloud storage services are able to ensure that their data has been saved in the cloud without tampering or manipulation. Experimental results are provided to validate the effectiveness of the proposed schemes.

scholarly journals Secure Data Deduplication in Cloud Environments

2021 ◽  
Author(s):  
Fatema Rashid
Keyword(s):  
Video Processing ◽  
Service Providers ◽  
Cloud Service ◽  
Error Correcting Codes ◽  
Digital Data ◽  
Data Deduplication ◽  
Data Types ◽  
Efficient Manner ◽  
Secure Data ◽  
Cloud Environments

With the tremendous growth of available digital data, the use of Cloud Service Providers (CSPs) are gaining more popularity, since these types of services promise to provide convenient and efficient storage services to end-users by taking advantage of a new set of benefits and savings offered by cloud technologies in terms of computational, storage, bandwidth, and transmission costs. In order to achieve savings in storage, CSPs often employ data dedplication techniques to eliminate duplicated data. However, benefits gained through these techniques have to balanced against users' privacy concerns, as these techniques typically require full access to data. In this thesis, we propose solutions for different data types (text, image and video) for secure data deduplication in cloud environments. Our schemes allow users to upload their data in a secure and efficient manner such that neither a semi-honest CSP nor a malicious user can access or compromise the security of the data. We use different image and video processing techniques, such as data compression, in order to further improve the efficiency of our proposed schemes. The security of the deduplication schemes is provided by applying suitable encryption schemes and error correcting codes. Moreover, we propose proof of storage protocols including Proof of Retrievability (POR) and Proof of Ownership (POW) so that users of cloud storage services are able to ensure that their data has been saved in the cloud without tampering or manipulation. Experimental results are provided to validate the effectiveness of the proposed schemes.

scholarly journals Selection of optimal data placement using cloud infrastructure

2021 ◽  
pp. 34-42
Author(s):  
Vladimir Meikshan ◽  
◽  
Natalia Teslya ◽  
Keyword(s):  
Mathematical Model ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Information Storage ◽  
Cloud Infrastructure ◽  
Digital Ecosystem ◽  
Cloud Service Providers ◽  
The Cost

Benefits of using cloud technology are obvious, their application is expanding, as a result, it determines the steady growth of demand. Cloud computing has acquired particular relevance for large companies connected with Internet services, retailing, logistics that generate large volume of business and other information. The use of cloud technologies allows organizing the joint consumption of resources, solving the problems of storing and transferring significant amounts of data. Russian consumer cooperation refers to large territory distributed organizations actively forming their own digital ecosystem. The issue of data storing and processing for consumer coo-peration organizations is very relevant. At the same time, the prices of cloud service providers are significantly different and require solving the problem of minimizing the cost of storing and transferring significant amounts of data. The application of the linear programming method is considered to select the optimal data storage scheme for several cloud service providers having different technical and economic parameters of the package (maximum amount of storage, cost of allocated resources). Mathematical model includes the equation of costs for data storing and transferring and restrictions on the amount of storage, the amount of data and its safety. Software tool that allows to perform numerical calculations is selected Microsoft Excel in combination with the "search for solutions" add-on. In accordance with the mathematical model, the conditions for minimizing the amount of cloud storage costs and the necessary restrictions are established. Initial data are set for three data forming centers, storages of certain size for five cloud service providers and nominal price for information storage and transmission. Calculations of expenses are performed in several variants: without optimization, with the solution of the optimization problem, with price increase by cloud service providers. Results of the calculations confirm the necessity to solve the problem of minimizing the cost of cloud services for corporate clients. The presented model can be expanded for any cost conditions as well as for different areas of cloud applications.

scholarly journals Improvement of Privacy and Security in Hybrid Cloud with Attribute Group Based Access Control

2019 ◽  
pp. 57-61
Author(s):  
Kayalvili S ◽  
Sowmitha V
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Security Requirements ◽  
Security And Privacy ◽  
Data Outsourcing ◽  
Privacy And Security ◽  
Control Approach

Cloud computing enables users to accumulate their sensitive data into cloud service providers to achieve scalable services on-demand. Outstanding security requirements arising from this means of data storage and management include data security and privacy. Attribute-based Encryption (ABE) is an efficient encryption system with fine-grained access control for encrypting out-sourced data in cloud computing. Since data outsourcing systems require flexible access control approach Problems arises when sharing confidential corporate data in cloud computing. User-Identity needs to be managed globally and access policies can be defined by several authorities. Data is dual encrypted for more security and to maintain De-Centralization in Multi-Authority environment.

scholarly journals A Privacy-Preserving Outsourcing Data Storage Scheme with Fragile Digital Watermarking-Based Data Auditing

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Xinyue Cao ◽  
Zhangjie Fu ◽  
Xingming Sun
Keyword(s):  
Data Storage ◽  
Digital Watermarking ◽  
Service Providers ◽  
Logistic Map ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Good Effect ◽  
Operation Speed ◽  
Storage Scheme ◽  
Data Auditing

Cloud storage has been recognized as the popular solution to solve the problems of the rising storage costs of IT enterprises for users. However, outsourcing data to the cloud service providers (CSPs) may leak some sensitive privacy information, as the data is out of user’s control. So how to ensure the integrity and privacy of outsourced data has become a big challenge. Encryption and data auditing provide a solution toward the challenge. In this paper, we propose a privacy-preserving and auditing-supporting outsourcing data storage scheme by using encryption and digital watermarking. Logistic map-based chaotic cryptography algorithm is used to preserve the privacy of outsourcing data, which has a fast operation speed and a good effect of encryption. Local histogram shifting digital watermark algorithm is used to protect the data integrity which has high payload and makes the original image restored losslessly if the data is verified to be integrated. Experiments show that our scheme is secure and feasible.

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