Cloud to cloud data migration using self sovereign identity for 5G and beyond

Aruna, M.; Hasan, Mohammad Kamrul; Islam, Shayla; Mohan, K.; Sharan, Preeta; Hassan, Rosilah

doi:10.1007/s10586-021-03461-7

Cited by 19 publications

(11 citation statements)

References 46 publications

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“…With the immense magnification of demand for services concerning cloud network, regulatory demands, there arise a requirement for a semi to fullyautomated self sovereign identity (SSI) implementation to minimize cost. A cryptographic method for data migration in a secured manner to and from thecloud network utilizing self sovereignty identity was implemented in [11]. With the involvement SSI peer-to-peer transactions, presence of TPA was no longer required, therefore reducing the cost.…”

Section: Related Workmentioning

confidence: 99%

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Bernstein Vazirani deep neural perceptron based certificateless signcryption for secured data communication in cloud

Selvam

Sujatha

Thanammal

2022

ijhs

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Present day evolutions in providing genuine security in the Cloud Computing Network havebeen made Certificateless Signcryption model exceedingly acceptable for several applications. However, security and privacy are the paramount area of interests in safeguarding data or data packet as they are said to be highly sensitive.Moreover, with conventional Certificateless Signcryption process found to be computationally laborious and with the discrete operation minimizing the advantages gained from smaller key size, data security is said to be compromised. To address on this issue, in this work, a novel method called, Bernstein Vazirani Deep Neural Perceptron-based Certificateless Signcryption (BVDNP-CS) for secured data communication in cloud computing network is proposed with multiple layers. The proposed BVDNP-CS method consists of one input layer, three hidden layers and one output layer. The BVDNP-CS method in the first layer obtains the data from personal cloud dataset. In the first hidden layer, with security parameterobtained as input, system parameters and master key are generated by means of Multi-linear mapping. In the second hidden layer, three keys, i.e., partial private key, private key and public key are generated by utilizing Bernstein–Vazirani Key Generation, therefore reducing the overhead incurred.

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Section: Related Workmentioning

confidence: 99%

“…This is mathematically expressed as given below. (11) Given the ciphertext ' ', on the other hand, the sender's identity ' '…”

Section: Multi-linear Mappingmentioning

confidence: 99%

Bernstein Vazirani deep neural perceptron based certificateless signcryption for secured data communication in cloud

Selvam

Sujatha

Thanammal

2022

ijhs

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“…Users store their identity data locally on the device and provide the required information to those who need it for verification. With the development of blockchains [4,5], blockchain-based SSI authentication protocols [6][7][8][9][10]were proposed recently. In 2018, Gra ¨ther et al [6] applied blockchain-based SSI to education certificate management to prevent education certificate forgery; Soltani et al [7] proposed a selfsovereign identity model for users onboarding on blockchain.…”

Section: Introductionmentioning

confidence: 99%

“…In 2018, Gra ¨ther et al [6] applied blockchain-based SSI to education certificate management to prevent education certificate forgery; Soltani et al [7] proposed a selfsovereign identity model for users onboarding on blockchain. In 2021, Abraham et al [8] introduced a SSI model utilizing identity wallets to ensure that the identity data control remains with the related user; Aruna et al [9] used a secure data migration to and from the cloud using SSI which facilitates peer-to-peer transactions; Figueroa-Lorenzo et al [10] presented a solution based on self-sovereign identity on hyperledger fabric blockchain. However, these current SSI authentication protocols pay little attention to privacy protection and the fine-grained access control of identity information.…”

Section: Introductionmentioning

confidence: 99%

A secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control based on federated blockchain

Ma¹,

Zheng²,

Zhao³

et al. 2022

PLoS ONE

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Self-sovereign identity authentication protocol is an active research topic in the field of identity authentication and management. However, the current SSI authentication protocols pay little attention to privacy protection and the fine-grained access control. Therefore, a secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control is proposed. Firstly, the formal model of SSI including the SDPP-SSI identity model and management model is presented. And then, based on the federated blockchain, the distributed identifier is used as a global identifier for users in the decentralized domain. Finally, the verifiable statement is encapsulated using a policy control signature supporting privacy protection to develop the user’s access control for identity registration in the centralized domain. Compared with the related work (Lin 2018, Zhu 2018, Stokkink 2018, Hammudoglu 2017, Othman 2017, Abraham 2018, Guan 2019, Lin 2019) from controllability, security, flexibility, privacy protection, authentication and fine-grained access control, the proposed SSI authentication protocol not only meets controllability, authentication, and flexibility, but also supports privacy protection and fine-grained access control.

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“…Each period of the data development interaction ought to be gotten, similar to data exposure, portrayal, and ordering of permission to the essential data. Appropriated capacity organizations are brought together [7] [8]. part in data movement plans and ought not to disregard orders.…”

Section: Introductionmentioning

confidence: 99%

Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models

Hashim

2022

International Journal of Computational and Applied Mathematics &Amp; Computer Science

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In relational and complex spreadsheets, relational and non-relational database models, high-speed data migration with scalable structure using visual Basic Excel programming language implementations with proposed migration model. One of the primary purposes behind making a point of interaction through the Visual Basic Application (VBA) is that most PC clients with logical preparation will currently know about Succeed and its significant capabilities (like arranging furthermore, plotting datasets). Even though Excel itself is in many cases utilized as an information storehouse by clients. The time factor, reliability, and credibility of migrating this data from one table to another through programming interfaces were measured using the link codes between the tables. In this paper, the migration and migration of homogeneous and heterogeneous data are investigated by using two types of different migration models of data to measure and match these data and the extent of their integration after migration. Specifies the target data for migration from the input tables in the Excel program to the target tables in larger databases. Furthermore, the two models (A, B) middleware provide an architecture that can be extended to support Relational database management systems (RDBMS) and other graphing databases. Experiments were performed using excel tables, both of which are related as source information bases, and as the data set for the source and target datasets, the migration time between these tables for the two models was calculated While retaining the same characteristics.

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Cloud to cloud data migration using self sovereign identity for 5G and beyond

Cited by 19 publications

References 46 publications

Bernstein Vazirani deep neural perceptron based certificateless signcryption for secured data communication in cloud

Bernstein Vazirani deep neural perceptron based certificateless signcryption for secured data communication in cloud

A secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control based on federated blockchain

Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models

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