Modeling software architecture design on data storage security in cloud computing environments

Cloud-based computation is known as the source architecture of the upcoming generation of IT enterprise. In context to up-coming trade solutions, the Information Technology sections are established under logical, personnel, and physical control, it transfers application software and large database to appropriate data centers, where security and management of database with services are not trustworthy fully. So this process may face many challenges towards society and organizations and that not been well understood over a while duration. This becomes one of the major challenges days today. So in this research, it focuses on security-based data storage using cloud, which plays one of the important aspects bases on qualities of services. To assure user data correctness in the cloud system, a flexible and effective distributed technique with two different salient features was examined by utilizing the token called homomorphic with erasure-coded data for distributed verification, based on this technique it achieved error data localization and integration of storage correctness. Also, it identifies server misbehaving, efficient, and security-based dynamic operations on data blocking such as data append, delete, and update methods. Performance analysis and security show the proposed method is more effective resilient and efficient against Byzantine failure, even server colluding attacks and malicious data modification attacks.

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Distributed verification protocols for data storage security in Cloud Computing

2012 International Conference on Communication, Information & Computing Technology (ICCICT) ◽

10.1109/iccict.2012.6398205 ◽

2012 ◽

Author(s):

Priodyuti Pradhan ◽

P. Syam Kumar ◽

Gautam Mahapatra ◽

R. Subramanian

Keyword(s):

Cloud Computing ◽

Data Storage ◽

Storage Security ◽

Distributed Verification

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PRICHAIN: A Partially Decentralized Implementation of UbiPri Middleware Using Blockchain

Sensors ◽

10.3390/s19204483 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4483 ◽

Cited By ~ 1

Author(s):

Iago Sestrem Ochôa ◽

Luis Augusto Silva ◽

Gabriel de Mello ◽

Bruno Alves da Silva ◽

Juan Francisco de Paz ◽

...

Keyword(s):

Internet Of Things ◽

Data Storage ◽

Personal Information ◽

Distributed Storage ◽

The Internet ◽

Storage Security ◽

User Data ◽

And Performance ◽

The Internet Of Things ◽

Different Levels

With the popularization of the Internet-of-Things, various applications have emerged to make life easier. These applications generate a large amount of user data. Analyzing the data obtained from these applications, one can infer personal information about each user. Considering this, it is clear that ensuring privacy in this type of application is essential. To guarantee privacy various solutions exist, one of them is UbiPri middleware. This paper presents a decentralized implementation of UbiPri middleware using the Ethereum blockchain. Smart contracts were used in conjunction with a communication gateway and a distributed storage service to ensure users privacy. The results obtained show that the implementation of this work ensures privacy at different levels, data storage security, and performance regarding scalability in the Internet of Things environments.

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An Efficient Distributed Verification Protocol for Data Storage Security in Cloud Computing

2013 2nd International Conference on Advanced Computing, Networking and Security ◽

10.1109/adcons.2013.46 ◽

2013 ◽

Cited By ~ 2

Author(s):

P. Syam Kumar ◽

R. Subramanian ◽

D. Thamizh Selvam

Keyword(s):

Cloud Computing ◽

Data Storage ◽

Storage Security ◽

Distributed Verification

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RAPTOR CODE BASED SECURE STORAGE IN CLOUD COMPUTING

International Journal of Computer and Communication Technology ◽

10.47893/ijcct.2016.1385 ◽

2016 ◽

pp. 276-280

Author(s):

R. MYTHILI ◽

P. PRADHEEBA ◽

P. RAJESHWARI ◽

S. PADHMAVATHI

Keyword(s):

Cloud Computing ◽

Data Storage ◽

Cloud Data ◽

Security Issues ◽

Secure Storage ◽

Distributed Verification ◽

Outsourced Data ◽

Proposed Model ◽

Cloud Data Storage ◽

Storage Correctness

The end of this decade is marked by a paradigm shift of the industrial information technology towards a pay-peruse service business model known as cloud computing. Cloud data storage redefines the security issues targeted on customer’s outsourced data. To ensure the correctness of users’ data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of raptor coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s).Using this new scheme it further support security and dynamic operations on data block. Our result shows that, our proposed model provides a secure storage for data in cloud.

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Enhanced Data Security from Single Clouds to Multiclouds

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i9.87 ◽

2018 ◽

Vol 6 (9) ◽

pp. 66

Author(s):

Umesh Banodha ◽

Praveen Kumar Kataria

Keyword(s):

Data Storage ◽

Network Connectivity ◽

Data Replication ◽

Recovery Process ◽

Cloud Environment ◽

Storage Security ◽

Cloud Data ◽

Replication Strategy ◽

Cloud Data Storage ◽

Data Files

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.

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Performance Evaluations of Distributed File Systems for Scientific Big Data in FUSE Environment

Electronics ◽

10.3390/electronics10121471 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1471

Author(s):

Jun-Yeong Lee ◽

Moon-Hyun Kim ◽

Syed Asif Raza Raza Shah ◽

Sang-Un Ahn ◽

Heejun Yoon ◽

...

Keyword(s):

Data Storage ◽

Scale Up ◽

File Systems ◽

Performance Evaluations ◽

Distributed File Systems ◽

Data Intensive Computing ◽

Data Intensive ◽

Tremendous Amount ◽

Computing Environments ◽

And Performance

Data are important and ever growing in data-intensive scientific environments. Such research data growth requires data storage systems that play pivotal roles in data management and analysis for scientific discoveries. Redundant Array of Independent Disks (RAID), a well-known storage technology combining multiple disks into a single large logical volume, has been widely used for the purpose of data redundancy and performance improvement. However, this requires RAID-capable hardware or software to build up a RAID-enabled disk array. In addition, it is difficult to scale up the RAID-based storage. In order to mitigate such a problem, many distributed file systems have been developed and are being actively used in various environments, especially in data-intensive computing facilities, where a tremendous amount of data have to be handled. In this study, we investigated and benchmarked various distributed file systems, such as Ceph, GlusterFS, Lustre and EOS for data-intensive environments. In our experiment, we configured the distributed file systems under a Reliable Array of Independent Nodes (RAIN) structure and a Filesystem in Userspace (FUSE) environment. Our results identify the characteristics of each file system that affect the read and write performance depending on the features of data, which have to be considered in data-intensive computing environments.

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An enhanced security tree to secure cloud data

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i1.1.8925 ◽

2017 ◽

Vol 7 (1.1) ◽

pp. 64 ◽

Cited By ~ 1

Author(s):

S. Renu ◽

S.H. Krishna Veni

Keyword(s):

Data Storage ◽

Binary Tree ◽

Data Encryption ◽

Third Party ◽

Data Outsourcing ◽

Cloud Data ◽

Security Issues ◽

Security Services ◽

Computing Services ◽

User Data

The Cloud computing services and security issues are growing exponentially with time. All the CSPs provide utmost security but the issues still exist. Number of technologies and methods are emerged and futile day by day. In order to overcome this situation, we have also proposed a data storage security system using a binary tree approach. Entire services of the binary tree are provided by a Trusted Third Party (TTP) .TTP is a government or reputed organization which facilitates to protect user data from unauthorized access and disclosure. The security services are designed and implemented by the TTP and are executed at the user side. Data classification, Data Encryption and Data Storage are the three vital stages of the security services. An automated file classifier classify unorganized files into four different categories such as Sensitive, Private, Protected and Public. Applied cryptographic techniques are used for data encryption. File splitting and multiple cloud storage techniques are used for data outsourcing which reduces security risks considerably. This technique offers file protection even when the CSPs compromise.

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