Hydrocarbon Processing - November 2022 - 14

Digital Technologies
the public key and is shared with any party. The decryption key
must remain private and serves only for data decryption. The
owner of the private key is the only entity capable of decrypting
the data encrypted with its corresponding public key.
The HE idea was introduced in 1978 by Rivest, et al.,1
but
no true fully HE scheme was developed for years. However,
research and improvement have increased in the last decade.
In 2009, Gentry2
made a breakthrough by specifying the first
fully HE scheme allowing summing and multiplying ciphertexts.
Many encryption schemes were then specified and regularly
optimized with the recognized 4th generation of the FHE
schemes (CKKS scheme in 2016). With these improvements,
it has been calculated that the speed of HE execution was increasing
by eight times every year between 2011 and 2021.3
This fast-track improvement of the technology has made it applicable
to daily life use in recent years.
Examples of already implemented HE include:
* Critical infrastructure monitoring, such as electrical
network load and balance
* Health data, including sharing private medical records
for statistical studies
* " Pay as you drive " insurance with an attached analytical
device that gauges driving style
* Passport face recognition at the airport.
In its current state, HE supports the basic mathematical operations
of summation and multiplication. This opens a wide
variety of applications, as these two operations are sufficient to
define a large spectrum of algebra.
However, HE requires significant computational resources
to perform operations within the encrypted space. The
computation time of a single simple equation may take a few
seconds to perform-this is the cost for the high privacy proposed
by HE.
Due to these limitations, the use of HE must be carefully investigated
to ensure selecting the most adequate HE algorithm
for a given application. In the energy industry, this technology
is of particular interest in the use of production data, which are
usually considered as extremely sensitive information as their
disclosure may impact companies' share or product prices.
This sensitivity of production data is a real showstopper for
the implementation of digital services to operations, as all inputs
to these services must remain within the company's operating
information management ecosystem. Therefore, subcontracting
specialized computation to vendors or contractors is
not considered an option by operating companies.
A three-party scheme. Using HE, it becomes possible to
utilize a scheme that includes up to three different parties in a
straightforward way. The first party is the industrial site/owner
of the production data. This first party is interested in using
external expertise resources but does not wish to disclose the
production data. The second party is a vendor or contractor
that has developed internal expertise and is willing to provide
results in a near real-time manner to the first party; however,
the second party wishes to retain its intellectual property on
the knowledge. Lastly, the third party possesses huge processing
capabilities and is willing to host the near real-time service.
This overall scheme is outlined in FIG. 2, which illustrates
how energy industry benefits can be leveraged from the HE
to run near real-time online processes and operations analysis
without disclosing production data.
The protocol can be declined in several two-party schemes,
considering that two of the three mentioned parties are the
same. Each of these two-party schemes would serve different
purposes, such as confidentiality during cloud computing or
confidentiality of algorithms and data.
The capacity to treat production data in near real time while
maintaining the privacy of the production data is quite appealing
to the energy industry, and enables the development
of digital services based on data reconciliation and analysis.
However, even if the technology is answering some of the key
questions for this kind of service, it must still prove effective in
the context of the energy industry.
Partnership in development project. The authors' companies
partnered in a development project to evaluate the application
of HE to a realistic problem in the energy industry.
A case study was selected regarding the monitoring and production
tracking of a debutanizer column. A process dynamic
simulation model of the asset was developed providing the
data from the industrial site. In addition, some computation
to be applied through the homomorphically encrypted program
was defined.
At the early stage of the project, two key issues were soon
highlighted. The first issue is that results from the homomorphic
calculations must be contextualized in time for a good
understanding of the results. The second issue deals with the
kind of data that is generated in our industry.
For contextualization, the issue was easily overcome by
adding a time stamping on the data. Therefore, even during a
steady operation of the plant that would generate two identical
sets of process conditions otherwise, the external observer
would not witness status quo information.
In the energy industry, engineers and operators are familiar
FIG. 2. Three-party confidentiality scheme.
14 NOVEMBER 2022 | HydrocarbonProcessing.com
with working with a broad range of real values to characterize
plant behavior. The common feature for all already developed
applications is that the encrypted input data are minimal in
terms of digital space. They are mostly coded over short integer
data when they are not binary. With HE, the computation time
will be related to the number of bits required to represent the
information. An initial assessment resulted in several minutes
for a sum product calculation when encrypting bits separately
using a binary plain text space. Further development with encryption
schemes supporting modular arithmetic with large
plain texts brought a sharp decrease in calculation time (from
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