Cloud Secured Protocol based on Partial Homomorphic Encryptions

Derfouf, Mostapha; Eleuldj, Mohsine

doi:10.1109/cloudtech.2018.8713353

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…Homomorphic Encryption: This is a technique that allows computations to be performed on encrypted data without decrypting them. This technique ensures that the data remain encrypted throughout the computation process, thus preserving the privacy of the data [2][3][4][5][6][7][8][9][10][11].…”

Section: Privacy-preservation In Deep Learningmentioning

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: Privacy-preservation In Deep Learningmentioning

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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“…In the aspect of data security privacy protection, secure multi-party computation based on homomorphic encryption has become more and more mainstream to protect data privacy [21]. Mostapha Derfouf et al proposed a security protocol based on partial homomorphic encryption [22], and compared the protocol with the fully homomorphic encryption protocol, and analyzed the advantages and disadvantages of the two schemes. Effectively solving the security challenges in cloud computing is the foundation of establishing the Industrial Internet of Things(IIoT) [23].…”

Section: Related Workmentioning

confidence: 99%

An Effective Security Comparison Protocol in Cloud Computing

Chen

Tao

et al. 2022

Preprint

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Secure comparison protocol is an important branch of secure multi-party computation(SMPC), which compares the size of input data without disclosing any information between participants. The development of cloud computing provides an application platform for SMPC, but it also brings new challenges. In cloud computing with SMPC, clients need to process their own data and submit the processed data to a cloud server, which then performs the computation. In this process, not only the clients need to maintain an honest state at all times, but sensitive data on the cloud server side may also be exposed. In this paper, zero-knowledge proof and homomorphic encryption techniques are used to improve Damgård-Geisler-KrØigaard(DGK) comparison protocol. The improved secure comparison protocol can not only safely calculate private data, but also be applicable to malicious participant model. Finally, the security analysis shows that the proposed scheme not only ensures the privacy security of participants, but also ensures the data fairness of comparison protocols.

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“…Like any encryption schema, HE includes four functions when applying it, these functions are key generation, encryption, evaluation, and decryption [49], [50]. Mathematically, HE means translation of one data set to an alternative one, without losing its relation between them [17].…”

Section: Definitionmentioning

confidence: 99%

“…HE has been classified into three types depending on the number of mathematical operations that can be performed. These types are [46], [49], [50], [53], [54]: − Partial HE: Performs addition or multiplication operation (not both). − Somewhat HE: Performs a bounded number of addition and multiplication operations.…”

Section: Categoriesmentioning

confidence: 99%

From cloud computing security towards homomorphic encryption: A comprehensive review

Mohammed

Taha

2021

TELKOMNIKA

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Cloud computing" is a new technology that revolutionized the world of communications and information technologies. It collects a large number of possibilities, facilities, and developments, and uses the combining of various earlier inventions into something new and compelling. Despite all features of cloud computing, it faces big challenges in preserving data confidentiality and privacy. It has been subjected to numerous attacks and security breaches that have prompted people to hesitate to adopt it. This article provided comprehensive literature on the cloud computing concepts with a primary focus on the cloud computing security field, its top threats, and the protection against each one of them. Data security/privacy in the cloud environment is also discussed and homomorphic encryption (HE) was highlighted as a popular technique used to preserve the privacy of sensitive data in many applications of cloud computing. The article aimed to provide an adequate overview of both researchers and practitioners already working in the field of cloud computing security, and for those new in the field who are not yet fully equipped to understand the detailed and complex technical aspects of cloud computing.

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Cloud Secured Protocol based on Partial Homomorphic Encryptions

Cited by 8 publications

References 6 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

An Effective Security Comparison Protocol in Cloud Computing

From cloud computing security towards homomorphic encryption: A comprehensive review

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