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1. CLOUD BANKING
DEVELOPMENT BASED ON
FULLY HOMOMORPHIC
ENCRYPTION
IHSAN JABBAR
SUPERVISERS:
PROF. SAAD ALSAAD
PROF. RADHI A. ZABOON

2. INTRODUCTION
• Nowadays technological advances indicate a dramatic growth of digital content.
• This explosion of the digital universe continues to increase the demand for new
storage and network utilities, along with an increasing need for more cost-effective
usage of storage capacities and network bandwidth for data transfer.
• The use of remote storage systems is gaining an expanding interest, namely the
cloud storage based services, since they provide profitable architectures.
• These architectures support the transmission, storage, and intensive computation of
outsourced data in a pay per use business model.
• Cloud computing is an appropriate solution for enterprises looking for flexible,
economic and feasible computing services for their daily activities
• Storage is an example of a cloud computing service, whereby users can store their
data that is maintained by a cloud service provider (CSP).

3. PROBLEM STATEMENT
• The main issue associated with a cloud storage service is security regarding
data privacy and confidentiality since data security is an important aspect of a
good-quality storage service.
• Cloud users do not have full control over their data, thus, cloud computing is
not fully trustable.
• The risks of personal privacy protection and data leakage are the main concerns
of individuals and enterprises before migrating their data to cloud storage
• Therefore, they are required to save an encrypted version of user’s data on their
storage.
• When cloud user wants to perform some computations on encrypted data, data
should be decrypted.
• Homomorphic encryption allows to perform computations directly on encrypted
data

4. WHAT IS HOMOMORPHIC ENCRYPTION
Homomorphic encryption systems are used to perform operations on encrypted
data without knowing the private key (without decryption), the client is the only
holder of the secret key. When we decrypt the result of any operation, it is the
same as if we had carried out the calculation on the raw data.

5. TYPES OF HOMOMORPHIC ENCRYPTION

6. TYPES OF HOMOMORPHIC ENCRYPTION
• All of PHE schemes allow homomorphic computation of only one operation,
either addition or multiplication, on encrypted date, except the boneh-goh-
nissim scheme which supports performing unlimited number of addition
operation but only one multiplication (SHE).
• The constructing of a scheme that allows one to compute arbitrary computation
(a scheme should allow an unlimited number of both addition and multiplication
operations) over encrypted data has remained a central open problem in
cryptography for more than 30 years and thought to be impossible until 2009,
when craig gentry proposed the first plausible construction of a fully
homomorphic scheme (FHE).

7. FULLY HOMOMORPHIC ENCRYPTION
• Fully homomorphic encryption (FHE) is the most sophisticated homomorphic
encryption scheme which allows to evaluate arbitrary functions on ciphertexts.

8. FULLY HOMOMORPHIC ENCRYPTION AND
CLOUD
• Cloud computing is the umbrella term for delivering services via the internet. It
enables enterprises and individuals to access services such as virtual machines,
storage, or applications on demand.
• In order to solve the problem of data security in cloud computing system, fully
homomorphic encryption can be used.

9. FULLY HOMOMORPHIC ENCRYPTION AND
CLOUD

10. BANK SERVICES IN THE CLOUD
• The use of cloud services for banks is considered a dangerous matter to some
extent because to this day storing data on the cloud is not considered a safe
matter because when the data is uploaded to the cloud, control over customer
data (such as account numbers, deposits, etc.) is lost.
• But on the other hand, there are many reasons makes banks and other
institutions to use cloud services, whether public or private, including
scalability, agility and saving many costs, but these benefits come with risks
related to data security, you should consider these risks when using cloud
services.
• Fully homomorphic encryption can be used to encrypt bank users data, besides
it allows to perform arbitrary computations on these date.

11. RELATED WORK
• Rivest et al. (1978) proposed first homomorphic encryption schema and were
partially homomorphic encryption (PHE).
• A fully homomorphic encryption (FHE) scheme suggested by Gentry (2009),
which allows calculating of any number of addition and multiplication, hence
compute arbitrary functions of encrypted data. Nevertheless, the scheme was
based on Somewhat Homomorphic Encryption (SWHE), which increases the
length and noise of ciphertext when calculation performs on the ciphertext.
• Consequently, van Dijk et al. (2010) have introduced FHE scheme that used
elementary modular arithmetic and used Gentry’s techniques to convert SWHE
cryptosystem to FHE scheme.

12. RELATED WORK CONT…
• In addition, smart and vercauteren (2010) have presented an improved version
of smart- vercauteren encryption schema. This schema was allowed several
times decrease the ciphertext and keys lengths.
• Moreover, a HE scheme which is security dependent on the hardness of large
integer factorization has been proposed by Xiao et al. (2012).
• Alattas and Elleithy (2013) have presented the application of algebraic
homomorphic encryption mechanism and it was aiming at enhancing its
security.
• In addition, IBM has released a software package named HElib in 2013.

13. RELATED WORK CONT…
• Hayward and chiang (2015) have improved gentry’s encryption in parallel processing
and they have tested it in a private cloud domain.
• Moreover, SAM which is an FHE scheme over integers has been implemented by
shihab and makki (2018).
• Mert et al. (2020) presented two hardware architectures optimized for accelerating
the encryption and decryption operations of the BFV/HE scheme with high
performance polynomial multipliers.
• Mohammed and Abed (2020) proposed a novel framework and an algorithm for
securing cloud data at rest.
• Despite all the works presented previously, the randomness and robustness of the
secret keys remain an open problem in the area of FHE.

14. REFRENCES
• Acar A, aksu H., Uluagac A.S. And conti, M., 2018. A survey on homomorphic encryption schemes: theory and
implementation. ACM computing surveys, 51(4), PP -35.
• Cheon J choe lee D. Andson 2019. Faster linear transformations in helib, revisited. IEEE access 7 pp50595-50604.
• Gentry, C., 2009. Fully Homomorphic Encryption Using Ideal Lattices. In: Proceedings of the 41st Annual ACM
Symposium on Symposium on Theory of Computing STOC ’09, Bethesda, Maryland, USA.
• Li song DE chen sand lux, 2012. Simple fully homomorphic encryption scheme available in cloud computing. In:
2012 IEEE 2nd international conference on cloud computing and intelligence systems, hangzhou, china.
• Mohammed and abed, 2020. A symmetric based framework for securing cloud data at rest. Turkish journal of
electrical engineering and computes sciences 28®1© pp 347-361.
• RIVEST, R.L.; ADLEMAN, L. AND DERTOUZOS, M.L., 1978. ON DATA BANKS AND PRIVACY HOMOMORPHISMS. IN:
FOUNDATIONS OF SECURE COMPUTATION. ACADEMIA PRESS, CAMBRIDGE MASSACHUSETTS.PP169-179.
• SHIHAB, H. AND MAKKI, S., 2018. DESIGN OF FULLY HOMOMORPHIC ENCRYPTION BY PRIME MODULAR OPERATION.
TELFOR JOURNAL 102 PP118-122.
• VAN DIJK, M., GENTRY, C., HALEVI, S. AND VAIKUNTANATHAN, V., 2010. FULLY HOMOMORPHIC ENCRYPTION OVER
THE INTEGERS. ADVANCES IN CRYPTOLOGY EUROCRYPT, 2010 PP24-43.
• SMART, N. AND VERCAUTEREN, F., 2010. FULLY HOMOMORPHIC ENCRYPTION WITH RELATIVELY SMALL KEY AND
CIPHERTEXT SIZES. PUBLIC KEY CRYPTOGRAPHY, 2010, PP 420-443.