scholarly journals Fully Homomorphic Cipher Based on Finite Algebraic Structures

2019 ◽  
pp. 97-103
Author(s):  
Y. Ts. Alaverdyan ◽  
E. G. Satimova
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Homomorphic Encryption ◽  
Encryption Algorithm ◽  
Cloud Provider ◽  
Algebraic Structures ◽  
Encrypted Data ◽  
Cloud Data ◽  
Cryptographic Algorithm ◽  
Cloud Data Processing

A way to increase the robustness of a cryptographic algorithm toward unauthorized inversion can be obtained through application of non-commutative or non-associative algebraic structures. In this regard, data security became a great issue in adaptation of cloud computing over Internet. While in the traditional encryption methods, security to data in storage state and transmission state is provided, in cloud data processing state, decryption of data is assumed, data being available to cloud provider. In this paper, we propose a special homomorphism between self-distributed and non-associative algebraic structures, which can stand as a premise to construct a homomorphic encryption algorithm aimed at the cloud data security in processing state. Homomorphic encryption so developed will allow users to operate encrypted data directly bypassing the decryption.

scholarly journals SecureDBaaS Model for Accessing Encrypted Cloud Databases

2015 ◽  
Vol 16 (2) ◽  
pp. 333
Author(s):  
Palle Jagadeeswaraiah ◽  
M.R. Pavan Kumar
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Encryption Algorithm ◽  
Cloud Provider ◽  
Concurrent Execution ◽  
Cloud Database ◽  
Cloud Databases ◽  
Main Thing ◽  
Cloud User ◽  
The Web

<p>Cloud computing has recently emerged being a compelling paradigm that pertains to managing and delivering services over the web. The particular prevalent problem connected with cloud is confidentiality, security, as well as reliability etc., in which how the cloud provider assures. To recognize this, a novel architecture is usually introduced that will integrates cloud database services and as well executing concurrent operations on encrypted information. Also a new homomorphic encryption algorithm will likely be incorporated to offer confidentiality as well as concurrent execution of various SQL operations. This will be the first option supporting quite a few distributed clienteles to access encrypted cloud databases. One of main thing is that it eliminates advanced proxies in between cloud user and provider.The performance on the architecture is usually calculated by means of theoretical and practical results which are subjected to TPC-C benchmark standard tools for a number of clients as well as network latencies.</p>

scholarly journals Ensuring Efficient Data Storage using Fully Mature Homomorphic Encryption Technique in the Cloud Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 5333-5342
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Homomorphic Encryption ◽  
Cloud Provider ◽  
Cloud Environment ◽  
Remote Site ◽  
Encrypted Data ◽  
Cloud Server ◽  
Efficient Data ◽  
Security Gap

In cloud computing, user database is stored at remote site instead of user computer’s hard disk where the connection between remote site and user computer is provided by internet connection. As cloud computing essentially places data outside the custody of owner of data, it inexorably hosts security disputes. The distance among the physical and the client location of data generates a barrier as the data can be accessed by an unauthorized party and this would influence the solitude of client’s data. The utilization of traditional encryption systems to encrypt the data prior to transmitting to the cloud provider has been most extensively utilized technique to link this security gap. Be that as it may, the customer will require offering the private key to the server to unscramble the information in front of playing out the figuring’s fundamental. Homomorphic encryption techniques permits computations on encrypted data devoid of decryption. This paper deals with the utilization of Fully Mature Homomorphic Encryption (FMHE) to encode the client’s data on cloud server and as well it facilitates to perform required computations on the encrypted data

scholarly journals Modified Fully Homomorphic Encryption based on Parallel Processing in Cloud Computing

2021 ◽  
pp. 250-262
Author(s):  
Parth Tandel ◽  
Abhinav Shubhrant ◽  
Mayank Sohani
Keyword(s):  
Cloud Computing ◽  
Parallel Processing ◽  
Data Security ◽  
Privacy Protection ◽  
Homomorphic Encryption ◽  
Security And Privacy ◽  
Fully Homomorphic Encryption ◽  
Privacy And Security ◽  
Encrypted Data ◽  
Encryption Algorithms

Cloud Computing is widely regarded as the most radically altering trend in information technology. However, great benefits come with great challenges, especially in the area of data security and privacy protection. Since standard cloud computing uses plaintext, certain encryption algorithms were implemented in the cloud for security reasons, and ‘encrypted' data was then stored in the cloud. Homomorphic Encryption (HE), a modern kind of encryption strategy, is born as a result of this change. Primarily, the paper will focus on implementing a successful Homomorphic Encryption (HE) scheme for polynomials. Furthermore, the objective of the paper is to propose, produce and implement a method to convert the already implemented sequentially processing Homomorphic Encryption into parallel processing Homomorphic Encryption (HE) using a Parallel Processing concept (Partitioning, Assigning, Scheduling, etc) and thereby producing a better performing Homomorphic Encryption (HE) called Fully Homomorphic Encryption (FHE). Fully Homomorphic Encryption (FHE) is an encryption technique that can perform specific analytical operations, functions and methods on normal or encrypted data and can still perform traditional encryption results as performed on plaintext. The three major reasons for implementing Fully Homomorphic Encryption (FHE) are advantages like no involvement of third parties, trade-off elimination between privacy and security and quantum safety.

About Fully Homomorphic Encryption Improvement Techniques

2021 ◽  
pp. 1331-1351
Author(s):  
Ahmed El-Yahyaoui ◽  
Mohamed Daifr Ech-Cherif El Kettani
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Encryption Algorithm ◽  
End User ◽  
Fully Homomorphic Encryption ◽  
Encrypted Data ◽  
Cloud Server ◽  
Encryption Schemes ◽  
Multiple Clients

Fully homomorphic encryption schemes (FHE) are a type of encryption algorithm dedicated to data security in cloud computing. It allows for performing computations over ciphertext. In addition to this characteristic, a verifiable FHE scheme has the capacity to allow an end user to verify the correctness of the computations done by a cloud server on his encrypted data. Since FHE schemes are known to be greedy in term of processing consumption and slow in terms of runtime execution, it is very useful to look for improvement techniques and tools to improve FHE performance. Parallelizing computations is among the best tools one can use for FHE improvement. Batching is a kind of parallelization of computations when applied to an FHE scheme, it gives it the capacity of encrypting and homomorphically processing a vector of plaintexts as a single ciphertext. This is used in the context of cloud computing to perform a known function on several ciphertexts for multiple clients at the same time. The advantage here is in optimizing resources on the cloud side and improving the quality of services provided by the cloud computing. In this article, the authors will present a detailed survey of different FHE improvement techniques in the literature and apply the batching technique to a promising verifiable FHE (VFHE) recently presented by the authors at the WINCOM17 conference.

scholarly journals Opportunities and Challenges of Data Migration in Cloud

2021 ◽  
Vol 9 (1) ◽  
pp. 41-50
Author(s):  
Ruhul Amin ◽  
Siddhartha Vadlamudi
Keyword(s):  
Cloud Computing ◽  
Impact Analysis ◽  
Academic Research ◽  
Security Requirements ◽  
Data Migration ◽  
Cloud Provider ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Data ◽  
Cloud Migration

Cloud data migration is the process of moving data, localhost applications, services, and data to the distributed cloud processing framework. The success of this data migration measure is relying upon a few viewpoints like planning and impact analysis of existing enterprise systems. Quite possibly the most widely recognized process is moving locally stored data in a public cloud computing environment. Cloud migration comes along with both challenges and advantages, so there are different academic research and technical applications on data migration to the cloud that will be discussed throughout this paper. By breaking down the research achievement and application status, we divide the existing migration techniques into three strategies as indicated by the cloud service models essentially. Various processes should be considered for different migration techniques, and various tasks will be included accordingly. The similarities and differences between the migration strategies are examined, and the challenges and future work about data migration to the cloud are proposed. This paper, through a research survey, recognizes the key benefits and challenges of migrating data into the cloud. There are different cloud migration procedures and models recommended to assess the presentation, identifying security requirements, choosing a cloud provider, calculating the expense, and making any essential organizational changes. The results of this research paper can give a roadmap for data migration and can help decision-makers towards a secure and productive migration to a cloud computing environment.

Cloud Data Management Based on Cloud Computing Technology

2014 ◽  
Vol 543-547 ◽  
pp. 3573-3576
Author(s):  
Yuan Jun Zou
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Data Processing ◽  
Development Planning ◽  
Computer Data ◽  
Cloud Data ◽  
Computing Platform ◽  
Convergence Error ◽  
Cloud Computing Platform ◽  
Cloud Data Processing

Cloud computing, networking and other high-end computer data processing technology are the important contents of eleven-five development planning in China. They have developed rapidly in recent years in the field of engineering. In this paper, we combine parallel computing with the collaborative simulation principle, design a cloud computing platform, establish the mathematical model of cloud data processing and parallel computing algorithm, and verify the applicability of algorithm through the numerical simulation. Through numerical calculation, cloud computing platform can be divided into complex grids, and the transmission speed is fast, which is eight times than the finite difference method. The mesh is meticulous, which reaches millions. Convergence error is minimum, only 0.001. The calculation accuracy is up to 98.36%.

Cloud-based services and customer satisfaction in the small and medium-sized businesses (SMBs)

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shurui Gao ◽  
Weidong Meng
Keyword(s):  
Cloud Computing ◽  
Customer Satisfaction ◽  
Human Resources ◽  
Data Security ◽  
Cloud Services ◽  
It Infrastructure ◽  
Content Type ◽  
Cloud Data ◽  
Start Ups ◽  
It Knowledge

PurposeCloud-based technologies are reliably improving Information Technology (IT) environment incorporating changes and modifications to the present business structure. Cloud computing enables small and medium-sized businesses (SMBs) to organize and exchange pertinent data and information in real time. This study checks out the influence of cloud-based services (IT infrastructure, expenses of cloud services, cloud data security and IT knowledge of human resources) on customers' satisfaction in SMBs.Design/methodology/approachCloud computing offers a way to coordinate and share organizational and personal information and data. The adoption of cloud services is one of the most emerging technological advances in the current competitive business environment. Cloud-based services allow start-ups or SMBs to take advantage of technological advancements and respond more quickly to changing consumer demands. In the available literature, cloud computing has received a lot of attention. However, there is also a research gap in creating a paradigm that links the value development drivers in the electronic industry with the leveraging impact of cloud and intercloud computing resources for start-ups and SMBs. A hypothetical model was constructed based on a literature review, and the associations between the latent variables were investigated utilizing structural equations.FindingsFindings from the study confirmed the validity of the proposed model for customer satisfaction assessment. Besides, the results showed that customer satisfaction is affected by cloud-based services in SMBs. The results illustrated that IT infrastructure influences customer satisfaction significantly and positively, with a T-value of 2.42. Also, the results confirmed that the cost of cloud services with a T-value of 2.68 affects customer satisfaction significantly and positively. Cloud data security also impacts customer satisfaction with a T-value of 5.20. The results also showed that the IT knowledge of human resources affects customer satisfaction with a T-value of 3.01.Originality/valueThe main originality of this research is proposing a new conceptual model to assess the impact of cloud-based services on the satisfaction of the customers in SMBs.

About Fully Homomorphic Encryption Improvement Techniques

2019 ◽  
Vol 10 (3) ◽  
pp. 1-20
Author(s):  
Ahmed El-Yahyaoui ◽  
Mohamed Daifr Ech-Cherif El Kettani
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Quality Of Services ◽  
End User ◽  
Fully Homomorphic Encryption ◽  
Encrypted Data ◽  
Cloud Server ◽  
Encryption Schemes ◽  
Multiple Clients

Fully homomorphic encryption schemes (FHE) are a type of encryption algorithm dedicated to data security in cloud computing. It allows for performing computations over ciphertext. In addition to this characteristic, a verifiable FHE scheme has the capacity to allow an end user to verify the correctness of the computations done by a cloud server on his encrypted data. Since FHE schemes are known to be greedy in term of processing consumption and slow in terms of runtime execution, it is very useful to look for improvement techniques and tools to improve FHE performance. Parallelizing computations is among the best tools one can use for FHE improvement. Batching is a kind of parallelization of computations when applied to an FHE scheme, it gives it the capacity of encrypting and homomorphically processing a vector of plaintexts as a single ciphertext. This is used in the context of cloud computing to perform a known function on several ciphertexts for multiple clients at the same time. The advantage here is in optimizing resources on the cloud side and improving the quality of services provided by the cloud computing. In this article, the authors will present a detailed survey of different FHE improvement techniques in the literature and apply the batching technique to a promising verifiable FHE (VFHE) recently presented by the authors at the WINCOM17 conference.

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