A mixed homomorphic encryption scheme for secure data storage in cloud

Kangavalli, R.; Vagdevi, S

doi:10.1109/iadcc.2015.7154867

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…The closer the value is to 1, the more accurately the model describes the available data. The value of R 2 is calculated according to the following formula: R 2 = 1 − S res S tot (18) where S tot = ∑ n i=1 T i − T 2 and T = 1 n ∑ n i T i . The value of R 2 for each implementation depends on the degree of polynomial extrapolation.…”

Section: Extrapolationmentioning

confidence: 99%

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption

Babenko

Golimblevskaia

Tchernykh

et al. 2023

BDCC

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Homomorphic encryption (HE) is a promising solution for handling sensitive data in semi-trusted third-party computing environments, as it enables processing of encrypted data. However, applying sophisticated techniques such as machine learning, statistics, and image processing to encrypted data remains a challenge. The computational complexity of some encrypted operations can significantly increase processing time. In this paper, we focus on the analysis of two state-of-the-art HE matrix multiplication algorithms with the best time and space complexities. We show how their performance depends on the libraries and the execution context, considering the standard Cheon–Kim–Kim–Song (CKKS) HE scheme with fixed-point numbers based on the Microsoft SEAL and PALISADE libraries. We show that Windows OS for the SEAL library and Linux OS for the PALISADE library are the best options. In general, PALISADE-Linux outperforms PALISADE-Windows, SEAL-Linux, and SEAL-Windows by 1.28, 1.59, and 1.67 times on average for different matrix sizes, respectively. We derive high-precision extrapolation formulas to estimate the processing time of HE multiplication of larger matrices.

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Section: Extrapolationmentioning

confidence: 99%

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption

Babenko

Golimblevskaia

Tchernykh

et al. 2023

BDCC

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“…Our aim is to cover two security issues namely confidentiality and privacy of the data stored and to achieve our aim homomorphic encryption methods are used as they are highly capable of providing data security in terms of confidentiality and privacy. The proposed method is built upon considering BGV method as the basis [17] method and the basic functions of BGV method are as shown in In this work attempt is made to enhance the efficiency of BGV method by modifying the key switching matrix with the help of permutation and the metadata production is computed based on Elliptic Curve Cryptography method. The methodology of the proposed method is explained as follows.…”

Section: Work Donementioning

confidence: 99%

Untitled

2019

IJCCSA

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Cloud data storage is a model of data storage where data in its digital form is stored in logical pools across the physical storage which is distributed across multiple servers usually in diverse locations. The full physical environment is owned and managed by an organization called Cloud Service Provider (CSP). In this type of storage, the data is distributed and owned by third party, and there is risk of unauthorized access. This makes security, reliability, confidentiality and privacy of data more important when storage in cloud is thought of. Although there are methods available for providing security, much work is not done with emphasis on dynamic nature of the data. Hence securing the data while updating becomes important. In this paper, a method that ensures confidentiality of data stored in cloud using homomorphic encryption is presented. The paper also provides a technique to ensure confidentiality during data updates in cloud. The presented method includes byte level automorphism for ensuring data integrity and confidentiality. The tabulated experimental results show that the proposed method provides more secure frame work for ensuring confidentiality and integrity of data in cloud.

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“…This method is called Module Switching Technology. The formal method can be defined as follows: for an integer in the vector x and integer's q> p> m, x 'is defined as x' ← Scale (x, q, pr, r) and x 'is the vector R, which is closer (p / q .x, corresponding to x '= x mod r [2]…”

Section: He Schemes In Cloud Storage-challengesmentioning

confidence: 99%

“…service providers with the development language and iii) software is the service are the services in which client applications are run on the infrastructure provided by the service providers. For all these services, users do not need to manage or manage the cloud infrastructure, including the network, server, operating system, storage, and even application functions [2]. The fact that technology users use the services offered by service providers is partly due to the fact that confidentiality of data storage confidentiality is not fully known to users [3].…”

Section: Introductionmentioning

confidence: 99%

Novel Homomorphic Encryption Scheme in Cloud Computing

Veena¹,

Hanumanthappa²

2018

IJET

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Cloud computing is an indispensable technology for any business organization, such as banking, e-commerce, etc. Although technology has advantages in many areas; The protection of stored data is a major concern for all stakeholders in the architecture. Provide data security with respect to network security, control strategies and access to the service, data storage. Despite the efforts of service providers to build customer trust in data security, users need a passion for using technology for their business skills. Homomorphism coding is a data protection technique in which tasks can be performed on encrypted data themselves. In this article, we present an exploration of new homomorphism encryption methods with respect to data security and their use in cloud computing.

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A mixed homomorphic encryption scheme for secure data storage in cloud

Cited by 10 publications

References 14 publications

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption

Untitled

Novel Homomorphic Encryption Scheme in Cloud Computing

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