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 Storage and Communication Security in Cloud Computing Using a Homomorphic Encryption Scheme Based Weil Pairing

2020 ◽  
Vol 26 (1) ◽  
pp. 78-83
Author(s):  
Demet Cidem Dogan ◽  
Huseyin Altindis
Keyword(s):  
Cloud Computing ◽  
Elliptic Curve ◽  
Data Transfer ◽  
Homomorphic Encryption ◽  
Discrete Logarithm ◽  
Original Data ◽  
Bilinear Pairing ◽  
Encryption Scheme ◽  
Weil Pairing ◽  
Encrypted Data

With introduction of smart things into our lives, cloud computing is used in many different areas and changes the communication method. However, cloud computing should guarantee the complete security assurance in terms of privacy protection, confidentiality, and integrity. In this paper, a Homomorphic Encryption Scheme based on Elliptic Curve Cryptography (HES-ECC) is proposed for secure data transfer and storage. The scheme stores the data in the cloud after encrypting them. While calculations, such as addition or multiplication, are applied to encrypted data on cloud, these calculations are transmitted to the original data without any decryption process. Thus, the cloud server has only ability of accessing the encrypted data for performing the required computations and for fulfilling requested actions by the user. Hence, storage and transmission security of data are ensured. The proposed public key HES-ECC is designed using modified Weil-pairing for encryption and additional homomorphic property. HES-ECC also uses bilinear pairing for multiplicative homomorphic property. Security of encryption scheme and its homomorphic aspects are based on the hardness of Elliptic Curve Discrete Logarithm Problem (ECDLP), Weil Diffie-Hellman Problem (WDHP), and Bilinear Diffie-Helman Problem (BDHP).

Research perspectives on fully homomorphic encryption models for cloud sector

2021 ◽  
pp. 1-26
Author(s):  
Sonam Mittal ◽  
K.R. Ramkumar
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Homomorphic Encryption ◽  
Data Encryption ◽  
Cloud Services ◽  
Future Research ◽  
Public Cloud ◽  
Fully Homomorphic Encryption ◽  
Research Perspectives ◽  
Learning With Errors

As there is a continuous delivery of big data, the researchers are showing interest in the applications of cloud computing concerning privacy, and security. On the other hand, many researchers and experts of cybersecurity have commenced on a quest for improving the data encryption to the models of big data and applications of cloud computing. Since many users of the cloud become public cloud services, confidentiality turns out to be a more compound problem. To solve the confidentiality problem, cloud clients maintain the data on the public cloud. Under this circumstance, Homomorphic Encryption (HE) appears as a probable solution, in which the information of the client is encrypted on the cloud in such a process that it permits few manipulation operations without decryption. The main intent of this paper is to present the systematic review of research papers published in the field of Fully Homomorphic Encryption (FHE) over the past 10 years. The encryption scheme is considered full when it consists of plaintext, a ciphertext, a keyspace, an encryption algorithm, and a decryption algorithm. Hence, the review mostly concentrates on reviewing more powerful and recent FHE. The contributions using different algorithms in FHE like Lattice-based, integer-based, Learning With Errors (LWE), Ring Learning With Errors (RLWE), and Nth degree Truncated polynomial Ring Units (NTRU) are also discussed. Finally, it highlights the challenges and gaps to be addressed in modeling and learning about competent, effectual, and vigorous FHE for the cloud sector and pays attention to directions for better future research.

scholarly journals Homomorphic Encryption Using Enhanced BGV Encryption Scheme For Cloud Security

2018 ◽  
Vol 7 (03) ◽  
pp. 23785-23789
Author(s):  
S.V.Suriya Prasad ◽  
K. Kumanan
Keyword(s):  
Homomorphic Encryption ◽  
Cloud Service ◽  
Cloud Security ◽  
Encryption Scheme ◽  
Public Cloud ◽  
Fully Homomorphic Encryption ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Or Applications

Fully Homomorphic Encryption is used to enhance the security incase of un-trusted systems or applications that deals with sensitive data. Homomorphic encryption enables computation on encrypted data without decryption. Homomorphic encryption prevents sharing of data within the cloud service where data is stored in a public cloud . In Partially Homomorphic Encryption it performs either additive or multiplicative operation, but not both operation can be carried out at a same time. Whereas , in case of Fully Homomorphic Encryption both operations can be carried out at same time. In this model , Enhanced BGV Encryption Technique is used to perform FHE operations on encrypted data and sorting is performed using the encrypted data

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 Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Quanbo Qu ◽  
Baocang Wang ◽  
Yuan Ping ◽  
Zhili Zhang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Homomorphic Encryption ◽  
Encryption Scheme ◽  
Symmetric Encryption ◽  
Secret Key ◽  
Fully Homomorphic Encryption ◽  
Key Recovery ◽  
Key Recovery Attack ◽  
Outsourced Databases

Homomorphic encryption is widely used in the scenarios of big data and cloud computing for supporting calculations on ciphertexts without leaking plaintexts. Recently, Li et al. designed a symmetric homomorphic encryption scheme for outsourced databases. Wang et al. proposed a successful key-recovery attack on the homomorphic encryption scheme but required the adversary to know some plaintext/ciphertext pairs. In this paper, we propose a new ciphertext-only attack on the symmetric fully homomorphic encryption scheme. Our attack improves the previous Wang et al.’s attack by eliminating the assumption of known plaintext/ciphertext pairs. We show that the secret key of the user can be recovered by running lattice reduction algorithms twice. Experiments show that the attack successfully and efficiently recovers the secret key of the randomly generated instances with an overwhelming probability.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

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