Authors:
Khalil Hariss
1
;
Abed Ellatif Samhat
2
and
Maroun Chamoun
3
Affiliations:
1
Faculty of Engineering - CRSI, Lebanese University, Hadat, Beirut, Lebanon, Faculté D’Ingénierie - CIMTI, Université Saint Joseph, Mar Roukoz, Beirut and Lebanon
;
2
Faculty of Engineering - CRSI, Lebanese University, Hadat, Beirut and Lebanon
;
3
Faculté D’Ingénierie - CIMTI, Université Saint Joseph, Mar Roukoz, Beirut and Lebanon
Keyword(s):
Cloud Computing, Cloud Privacy, Fully Homomorphic Encryption, Domingo Ferrer, Learning with Error, Key Switching, Circuit Evaluation, Storage Overhead, Known Plain-text Attack, Polynomial Resultant.
Related
Ontology
Subjects/Areas/Topics:
Information and Systems Security
;
Security and Privacy in the Cloud
Abstract:
In this paper, we consider the privacy issue in cloud systems by using Homomorphic Encryption (HE) to provide secure computing at the cloud side. We use Domingo Ferrer (DF) homomorphic scheme to accomplish this task. Before implementing DF in a cloud scenario, we resolve its main problems. The two concerned problems are sensitivity to known plain-text attack and cipher-text dimension growth after homomorphic multiplication causing high storage overhead and reducing the scheme efficiency. DF is first made secure for cloud systems by making the scheme much more resistant to the concerned attack due to the change of the encryption procedure. Second, DF is made efficient for cloud computing by introducing a new technique, called Key Switching (KS). This technique reduces the high overhead by decreasing the extended cipher-text dimension obtained after a homomorphic multiplication and preserving the homomorphic behavior. While users’ privacy at the Cloud side is preserved with HE, KS tech
nique relies on publishing a matrix M. Different secret keys are encrypted within M based on the hardness of Learning With Error (LWE). A deep crypt-analysis and implementations under Python using SageMath Library are done in order to validate the efficiency of our proposal.
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