Hydrocarbon Processing - November 2022 - 13

Digital
Technologies
F. REY and M. SANCHEZ, Technip Energies, Paris, France; and
A. BOUDGUIGA, Université Paris-Saclay, CEA-List, Paris, France
The benefits of homomorphic encryption: A
technological enabler for digital services to operations
Among the cryptographic technologies under development
in various industries, homomorphic encryption (HE) possesses
the attractive feature of allowing computation within
the encrypted domain. Encrypted data cannot only be transferred
and stored, but also used in the secure encrypted state.
This state-of-the-art technology has evolved rapidly over the
past decade with new breakthroughs every year since the first
functional implementation in 2009. The technology has already
been proposed for face recognition and in other domains
where a high level of privacy is mandatory.
This article presents the main principles of HE, as well as
the benefits that can be leveraged from this technology for the
energy industry. It also provides information on the specific
challenges faced in its implementation in our industry.
With the advent of Industry 4.0, a company's digital transformation
embeds the exploitation of all available plant data to
enhance monitoring, planning and optimization of operating
parameters, maximizing the production rate at minimal cost.
As an example, predictive maintenance solutions analyze performance
and operating data from rotating equipment to detect
any potential failure as early as possible using tools that combine
machine-learning and artificial intelligence (AI) methods.
Often overlooked or underused, plant operating data constitutes
an important and full-fledged asset that should be properly
valued and secured internally or by third-party expertise.
In cases where data cannot be used internally and must be
transmitted to an external service provider, data owners can be
reluctant to share such confidential information in plain text
with a third party for various reasons. This data can include
protected intellectual property on the company's facilities, financial
statements and results, and sensitive information with
national security implications.
How can we guarantee a company's confidential data can
be outsourced safely by certifying the content will not be
" readable " by a third party in charge of its processing?
There are many competing technologies for data encryption.
Among the main technologies, symmetric cryptography,
such as advanced encryption standard (AES), and asymmetric
cryptography, such as RSA or El Gamal, are widely used
when navigating the web and for online payment. These cryptography
algorithms are recognized for their fast computation
time while providing an important level of security for data at
transit and data at rest. However, data must be deciphered to
be of any use in computation. As such, these algorithms are
not fit for the use of confidential data by a third party.
Therefore, other algorithms are proposed for more advanced
applications. As an example, multiparty computation
(MPC) is adopted in digital asset protection and cryptocurrency.
Though MPC allows the performance of mathematical
operations on encrypted data, the result of the computation
can be available to all parties. One of the specifics of the MPC
scheme is that it also requires an elevated level of cooperation
between parties, as the computation algorithm must be shared.
When compared to these technologies (i.e., classical cryptographic
algorithms AES or RSA), HE adds computation
confidentiality to data confidentiality at transit and at rest
ensured by AES or RSA. It also alleviates the communication
overheads introduced when using MPC.
Enabling safe and secure computations. HE is a form of
encryption that allows computation on encrypted data, generating
an encrypted result that, when decrypted, matches the
result of the operations as if it had been performed on plain
text. This means encrypted data can be securely and safely outsourced
for computation by third parties.
In a real case example, " Alice " will encrypt and transmit her
sensitive data to " Bob, " who is in charge of data analysis and
computation. The homomorphic property of the encryption
algorithm allows Bob to perform these calculations directly on
the encrypted data and obtain an encrypted result. The latter
is an encrypted version of the result that would be recovered
if Bob's computation were done directly on Alice's plain texts.
As shown in FIG. 1, Alice receives from Bob the encrypted
results of the operation. Alice uses the decryption key to recover
the results and then exploit them. Only Alice, owner of
the private key used for decryption, will be able to read and
understand the results of the calculation performed by Bob.
Bob, in charge of the data computation, will never have access
to the data in plain text, neither input nor calculation results.
On the other side, the details of calculation algorithms remain
Bob's intellectual property and are not disclosed to Alice.
HE can be symmetric or asymmetric. In the first case, the encryption
and decryption keys will be the same secret key. Meanwhile,
in the second case, the encryption and decryption keys
will be different but related. The encryption key is also called
FIG. 1. Principle of homomorphic encryption.
Hydrocarbon Processing | NOVEMBER 2022 13
Hydrocarbon Processing - November 2022

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