Research on Full Homomorphic Encryption Algorithm for Integer in Cloud Environment

2019 ◽  
pp. 109-117
Author(s):  
Lijuan Wang ◽  
Lina Ge ◽  
Yugu Hu ◽  
Zhonghua He ◽  
Zerong Zhao ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Encryption Algorithm ◽  
Cloud Environment

Recent Advances Delivered in Mobile Cloud Computing's Security and Management Challenges

2020 ◽  
pp. 21-43
Author(s):  
Christos Stergiou ◽  
Kostas E. Psannis
Keyword(s):  
Cloud Computing ◽  
Mobile Device ◽  
Mobile Cloud Computing ◽  
New Method ◽  
Encryption Algorithm ◽  
Mobile Cloud ◽  
Cloud Environment ◽  
Computational Power ◽  
Access To Data ◽  
Aes Encryption Algorithm

Mobile cloud computing provides an opportunity to restrict the usage of huge hardware infrastructure and to provide access to data, applications, and computational power from every place and in any time with the use of a mobile device. Furthermore, MCC offers a number of possibilities but additionally creates several challenges and issues that need to be addressed as well. Through this work, the authors try to define the most important issues and challenges in the field of MCC technology by illustrating the most significant works related to MCC during recent years. Regarding the huge benefits offered by the MCC technology, the authors try to achieve a more safe and trusted environment for MCC users in order to operate the functions and transfer, edit, and manage data and applications, proposing a new method based on the existing AES encryption algorithm, which is, according to the study, the most relevant encryption algorithm to a cloud environment. Concluding, the authors suggest as a future plan to focus on finding new ways to achieve a better integration MCC with other technologies.

scholarly journals Privacy-Preserving Oriented Floating-Point Number Fully Homomorphic Encryption Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Shuangjie Bai ◽  
Geng Yang ◽  
Jingqi Shi ◽  
Guoxiu Liu ◽  
Zhaoe Min
Keyword(s):  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Expansion Ratio ◽  
Public Key ◽  
Floating Point ◽  
Encryption Scheme ◽  
Cloud Environment ◽  
Fully Homomorphic Encryption ◽  
Point Number ◽  
Floating Point Number

The issue of the privacy-preserving of information has become more prominent, especially regarding the privacy-preserving problem in a cloud environment. Homomorphic encryption can be operated directly on the ciphertext; this encryption provides a new method for privacy-preserving. However, we face a challenge in understanding how to construct a practical fully homomorphic encryption on non-integer data types. This paper proposes a revised floating-point fully homomorphic encryption scheme (FFHE) that achieves the goal of floating-point numbers operation without privacy leakage to unauthorized parties. We encrypt a matrix of plaintext bits as a single ciphertext to reduce the ciphertext expansion ratio and reduce the public key size by encrypting with a quadratic form in three types of public key elements and pseudo-random number generators. Additionally, we make the FFHE scheme more applicable by generalizing the homomorphism of addition and multiplication of floating-point numbers to analytic functions using the Taylor formula. We prove that the FFHE scheme for ciphertext operation may limit an additional loss of accuracy. Specifically, the precision of the ciphertext operation’s result is similar to unencrypted floating-point number computation. Compared to other schemes, our FFHE scheme is more practical for privacy-preserving in the cloud environment with its low ciphertext expansion ratio and public key size, supporting multiple operation types and high precision.

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