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

PpBAC

2018 ◽  
Vol 30 (4) ◽  
pp. 14-31 ◽  
Author(s):  
Suyel Namasudra ◽  
Pinki Roy
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Control Method ◽  
Cloud Environment ◽  
Authorized User ◽  
Control Scheme ◽  
Control Schemes ◽  
Confidential Data ◽  
Efficient Data

This article describes how nowadays, cloud computing is one of the advanced areas of Information Technology (IT) sector. Since there are many hackers and malicious users on the internet, it is very important to secure the confidentiality of data in the cloud environment. In recent years, access control has emerged as a challenging issue of cloud computing. Access control method allows data accessing of an authorized user. Existing access control schemes mainly focus on the confidentiality of the data storage. In this article, a novel access control scheme has been proposed for efficient data accessing. The proposed scheme allows reducing the searching cost and accessing time, while providing the data to the user. It also maintains the security of the user's confidential data.

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.

scholarly journals Towards Query Processing Over Homomorphic Encrypted Data in Cloud

2019 ◽  
Vol 26 (4) ◽  
pp. 65-72
Author(s):  
Lina Samir Malouf
Keyword(s):  
Cloud Computing ◽  
Query Processing ◽  
Data Storage ◽  
New Technologies ◽  
Homomorphic Encryption ◽  
Management Systems ◽  
Computing Technology ◽  
Online Service ◽  
Encrypted Data ◽  
Advanced Technologies

With data growth very fast, the need for data storage and management in the cloud in a secure way is rapidly increasing, leading developers to find secure data management solutions through new technologies. One of the most advanced technologies at present is cloud computing technology that functions as an online service. Cloud computing technology relies on an external provider to provide online demand services. On the other hand, this technology is pay-for-use technology which means that the user must pay for each service provided by the provider. When we have a look back at the literature, we can find that regular database management systems with query processing specifications do not meet the requirements in cloud computing. This paper focuses on homogeneous coding, which is used primarily for knowledge security within the cloud. Homomorphic encryption has been clarified because of encryption technology in which specific operations can be managed on encrypted data information.

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 A Novel Secure Scheme for Supporting Complex SQL Queries over Encrypted Databases in Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Guoxiu Liu ◽  
Geng Yang ◽  
Huaqun Wang ◽  
Yang Xiang ◽  
Hua Dai
Keyword(s):  
Cloud Computing ◽  
Security Analysis ◽  
Efficiency Evaluation ◽  
Cloud Environment ◽  
Encrypted Data ◽  
Multiple Encryption ◽  
Cloud Server ◽  
Encryption Schemes ◽  
Database As A Service ◽  
Order Comparison

With the advance of database-as-a-service (DaaS) and cloud computing, increasingly more data owners are motivated to outsource their data to cloud database for great convenience and economic savings. Many encryption schemes have been proposed to process SQL queries over encrypted data in the database. In order to obtain the desired data, the SQL queries contain some statements to describe the requirement, e.g., arithmetic and comparison operators (+, -, ×, <, >, and =). However, to support different operators (+, -, ×, <, >, and =) in SQL queries over encrypted data, multiple encryption schemes need to be combined and adjusted to work together. Moreover, repeated encryptions will reduce the efficiency of execution. This paper presents a practical and secure homomorphic order-preserving encryption (FHOPE) scheme, which allows cloud server to perform complex SQL queries that contain different operators (such as addition, multiplication, order comparison, and equality checks) over encrypted data without repeated encryption. These operators are data interoperable, so they can be combined to formulate complex SQL queries. We conduct security analysis and efficiency evaluation of the proposed scheme FHOPE. The experiment results show that, compared with the existing approaches, the FHOPE scheme incurs less overhead on computation and communication. It is suitable for large batch complex SQL queries over encrypted data in cloud environment.

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.

Lattice-Based Identity-Based Homomorphic Conditional Proxy Re-Encryption for Secure Big Data Computing in Cloud Environment

2017 ◽  
Vol 28 (06) ◽  
pp. 645-660 ◽  
Author(s):  
Chunguang Ma ◽  
Juyan Li ◽  
Weiping Ouyang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Sharing ◽  
Homomorphic Encryption ◽  
Encryption Scheme ◽  
Cloud Environment ◽  
Public Cloud ◽  
Encrypted Data ◽  
Identity Based ◽  
Big Data Computing

With the arrival of the era of big data, more and more users begin to adopt public cloud storage to store data and compute data. Sharing large amounts of sensitive data in the public cloud will arouse privacy concerns. Data encryption is a widely accepted method to prevent information leakage. How to achieve the cloud sharing and cloud computing of big data is a challenging problem. Conditional proxy re-encryption can solve cloud sharing, and homomorphic encryption can achieve cloud computing. In this paper, we combine conditional proxy re-encryption with homomorphic encryption to construct a lattice-based identity-based homomorphic conditional proxy re-encryption for secure big data computing in cloud environment. The scheme can not only realize the encrypted data sharing in the cloud, but also can realize the encrypted data computing in the cloud. That is, the homomorphic conditional proxy re-encryption scheme can homomorphically evaluate ciphertexts no matter ciphertexts are “fresh” or re-encrypted (re-encrypted ciphertexts can come from different identities). The constructed scheme modifies the homomorphic proxy re-encryption scheme of Ma et al. We also use the approximate eigenvector method to manage the noise level and decrease the decryption complexity without introducing additional assumptions. At last, we prove that the scheme is indistinguishable against chosen-plaintext attacks, key privacy secure and master secret secure.

scholarly journals Video Data Integrity Verification Method Based on Full Homomorphic Encryption in Cloud System

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Ruoshui Liu ◽  
Jianghui Liu ◽  
Jingjie Zhang ◽  
Moli Zhang
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Homomorphic Encryption ◽  
Data Integrity ◽  
Video Data ◽  
Verification Method ◽  
Whole Process ◽  
Integrity Checking ◽  
Verification Methods ◽  
Cloud Servers

Cloud computing is a new way of data storage, where users tend to upload video data to cloud servers without redundantly local copies. However, it keeps the data out of users' hands which would conventionally control and manage the data. Therefore, it becomes the key issue on how to ensure the integrity and reliability of the video data stored in the cloud for the provision of video streaming services to end users. This paper details the verification methods for the integrity of video data encrypted using the fully homomorphic crytosystems in the context of cloud computing. Specifically, we apply dynamic operation to video data stored in the cloud with the method of block tags, so that the integrity of the data can be successfully verified. The whole process is based on the analysis of present Remote Data Integrity Checking (RDIC) methods.

scholarly journals New Algorithms for Secure Outsourcing of Large-Scale Systems of Linear Equations

2020 ◽  
Vol 9 (5) ◽  
pp. 545-550
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Storage ◽  
Large Scale ◽  
Homomorphic Encryption ◽  
Linear Equations ◽  
Force Transmission ◽  
Large Scale Systems ◽  
Secure Outsourcing ◽  
Systems Of Linear Equations

Cloud computing is the on-request accessibility of computer system resources, specially data storage and computing power, without direct dynamic management by the client. In the simplest terms, cloud computing means storing and accessing data and programs over the Internet instead of your computer’s hard drive. Along the improvement of cloud computing, more and more applications are migrated into the cloud. A significant element of distributed computing is pay-more only as costs arise. Distributed computing gives strong computational capacity to the general public at diminished cost that empowers clients with least computational assets to redistribute their huge calculation outstanding burdens to the cloud, and monetarily appreciate the monstrous computational force, transmission capacity, stockpiling, and even reasonable programming that can be partaken in a compensation for each utilization way Tremendous bit of leeway is the essential objective that forestalls the wide scope of registering model for clients when their secret information are expended during the figuring procedure. Critical thinking is a system to arrive at the pragmatic objective of specific instruments that tackles the issues as well as shield from pernicious practices.. In this paper, we examine secure outsourcing for large-scale systems of linear equations, which are the most popular problems in various engineering disciplines. Linear programming is an operation research technique formulates private data by the customer for LP problem as a set of matrices and vectors, to develop a set of efficient privacypreserving problem transformation techniques, which allow customers to transform original LP problem into some arbitrary one while protecting sensitive input/output information. Identify that LP problem solving in Cloud component is efficient extra cost on cloud server. In this paper we are utilizing Homomorphic encryption system to increase the performance and time efficiency

scholarly journals Efficient verifiable fuzzy keyword search over encrypted data in cloud computing

2013 ◽  
Vol 10 (2) ◽  
pp. 667-684 ◽  
Author(s):  
Jianfeng Wang ◽  
Hua Ma ◽  
Qiang Tang ◽  
Jin Li ◽  
Hui Zhu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Efficiency Analysis ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Proposed Model ◽  
Cloud Server ◽  
Encryption Schemes ◽  
User Data ◽  
Fuzzy Keyword Search

As cloud computing becomes prevalent, more and more sensitive data is being centralized into the cloud by users. To maintain the confidentiality of sensitive user data against untrusted servers, the data should be encrypted before they are uploaded. However, this raises a new challenge for performing search over the encrypted data efficiently. Although the existing searchable encryption schemes allow a user to search the encrypted data with confidentiality, these solutions cannot support the verifiability of searching result. We argue that a cloud server may be selfish in order to save its computation ability or bandwidth. For example, it may execute only a fraction of the search and returns part of the searching result. In this paper, we propose a new verifiable fuzzy keyword search scheme based on the symbol-tree which not only supports the fuzzy keyword search, but also enjoys the verifiability of the searching result. Through rigorous security and efficiency analysis, we show that our proposed scheme is secure under the proposed model, while correctly and efficiently realizing the verifiable fuzzy keyword search. The extensive experimental results demonstrate the efficiency of the proposed scheme.

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