=Paper=
{{Paper
|id=Vol-2864/paper27
|storemode=property
|title=Intellectual Property Assurance Method for Digital University Ecosystem based on Blockchain Technology
|pdfUrl=https://ceur-ws.org/Vol-2864/paper27.pdf
|volume=Vol-2864
|authors=Oleksandr Kapliienko,Galyna Tabunshchyk,Tetiana Kapliienko,Carsten Wolff
|dblpUrl=https://dblp.org/rec/conf/cmis/KapliienkoTKW21
}}
==Intellectual Property Assurance Method for Digital University Ecosystem based on Blockchain Technology==
https://ceur-ws.org/Vol-2864/paper27.pdf
Intellectual property assurance method for digital university
ecosystem based on blockchain technology
Oleksandr Kapliienkoa, Galyna Tabunshchyka, Tetiana Kapliienkoa and Carsten Wolffb
a
National University "Zaporizhzhia Polytechnic", 64, Zhukovsky Street, Zaporizhzhya, 69063, Ukraine
b
Fachhochschule Dortmund, 23, Otto-Hahn-Str., Dortmund, 44227, Germany
Abstract
In the university digital ecosystem it is very important to have a proper process of collecting,
processing and storing the data about students educational results which could confirm the
level of the achieved outcomes within their study. In the paper authors provide an analysis of
the data which should be stored and existing system which are used for diploma verification.
According to the authors' research, the strategy for the digital transformation of the high
educational institutes education system should include the modernization of the management
of the intellectual property and learning outcomes (competencies and skills). To provide an
intellectual property assurance for the students’ documents there were chosen blockchain
technology. Intellectual property assurance method for digital university ecosystem based on
blockchain technology was proposed by the authors.
Keywords 1
Education, Intellectual property, Learning outcomes, Blockchain, Security, Decentralization,
eLearning
1. Introduction
The modern high educational institutes (HEIs) should ensure a study process in the relevant
professions and specialties according to the demands the labor market. The learning process should be
comfortable and based on the principles of academic integrity. The digital university infrastructure
should ensure safety and security for staff and students, specially ensure the intellectual property (IP)
of the created academic materials, as some if it according to the national law and regulation should be
stored from 5 to 10 years [1].
An important feature of the educational system is an implementation of the different learning
approaches and standards in different HEI even in one country, which also change year by year.
Accordingly, the presence of a diploma in the same specialty from different institutions and / or from
different years of graduation does not imply the presence of the same learning outcomes
(competencies and skills). It is also necessary to take into account that students could choose
alternative disciplines and internships within their study program, or have additional achievements in
the learning process.
To support a coherent and understandable system of an individual’s lifelong learning there should
be stored a sizable amount of data that needs to be saved for the diploma assurance.
There are a lot of requirements which are put forward for this data:
they must be ordered by the time of creation;
intellectual property and personal data must be protected from external access;
CMIS-2021: The Fourth International Workshop on Computer Modeling and Intelligent Systems, April 27, 2021, Zaporizhzhia, Ukraine
EMAIL: alexandr.kaplienko@gmail.com (O. Kapliienko); galina.tabunshchik@gmail.com (G. Tabunshchyk); bragina.zntu@gmail.com
(T. Kapliienko); carsten.wolff@fh-dortmund.de (C. Wolff)
ORCID: 0000-0003-2080-7875 (O. Kapliienko); 0000-0003-1429-5180 (G. Tabunshchyk); 0000-0001-8192-2397 (T. Kapliienko); 0000-
0003-3646-5240 (C. Wolff)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
the data that confirm the acquisition of certain skills and competencies must be located in the
public domain;
the data should be stored decentralized to avoid loss problems;
the data should be protected against falsifications, for example change protection or adding
faking data.
One of the options for meeting these requirements can be the use of blockchain technology, which
introduces immutability and trust to the decentralize data. This paper presents an approach for saving
education data based on the blockchain for ensuring the safety and reliability of storing information
about the entire learning process for each student (from admission stage to graduation with a HEIs
diploma).
2. State of the art
The primary reason for storing of the individual academic materials is the need to confirm the level
of education by a certain student (for example, bachelor's, master's degree). Until 2012 in Ukraine,
such confirmation was the physical presence of a state diploma, formed by the authorized agency. The
disadvantages of this approach were the possibility of forgery or loss of the diploma itself or its
supplementary.
In 2012 year, the Ukrainian government introduced the Unified State Electronic Database on
Education (USEDE), which is an automated system for collecting, registering, processing, storing and
protecting educational information [2]. Since that the diploma as a physical object is not the main
goal, the main achievement is the record in this database which confirms the presence of a degree of
education of a certain level in a certain specialty.
There are many similar systems and databases in the world that mainly pursue 2 goals:
obtaining data for statistics [3, 4, 5, 6];
confirmation of the authenticity of educational documents [7, 8, 9].
For example, the “UIS.Stat” is a product of the UNESCO Institute for Statistics (UIS), which is the
official and trusted source of internationally-comparable data on education, science, culture and
communication [3]. This system is a comprehensive browser for viewing and downloading the most
popular education data and indicators, such as [3]:
mean years of schooling;
number and rates of international mobile students (inbound and outbound);
number of students and enrolment rates by level of education;
graduation ratio from tertiary education;
out-of-school children, adolescents and youth (number);
percentage of graduates by field of education (tertiary education);
educational expenditure by nature of spending in public educational institutions;
government expenditure on education (amount);
survival rate by grade for primary education;
population of the official age / school age population;
official entrance age and theoretical duration by level of education (years) and etc.
The OECD.stat database [4] have the similar information provided by the Organization for
Economic Co-operation and Development (OECD). In this database there are also information about
graduation and entry rates, profile of graduates and new entrants, distribution of graduates and
entrants by field, and other indicators. The World Bank EdStats (Education Statistics) portal [5] and
Global Education [6] extensive data and analysis source for key topics and a “meta-entry" in
education with the visualizations and research. These data make it possible to determine the state of
education in a particular country by many different indicators, the progress of development of a
particular area, but described systems do not have the opportunity to confirm the level of education of
a particular graduate or student.
"DiplomaVerify" and "DegreeVerify" (National Student Clearinghouse Verification Services) [7]
gives possibility to instantly verify diplomas for high school graduates of USA (549 educational
institutions for this moment) and provides online verifications of college degrees and attendance.
“Nuffic” is the National Academic Recognition Information Centre for Holland [8], the goal of
which is to allow to find an equivalent Dutch level of diploma from another country.
The [9] is a service of the "Institut National des Sciences Appliquées" (INCA) of Toulouse that
allows to authenticated all INSA diplomas using Prooftag. Prooftag is a security seal and electronic
tag found on INSA’s diplomas, which contains a unique code that acts as an electronic birth
certificate [10].
The need for the presented systems arose due to the presence of progressive and low-cost scanning
and printing technologies, which increase the number of fake academic certificates. These systems
represent cooperation within a country, organization or institution.
Since document verification is very important to assure that the diploma is official, some
organizations have developed and are presenting their approaches to this systematic process. For
example, Documentorum is a global initiative and a new approach to the issuance, registration and
verification of certificates and diplomas [11]. It was developed using Hyperledger technology (an
open-source collaboration created to advance cross-industry blockchain technologies). It allows
students to collect all of their academic data in one place, where it is protected from theft and
fraud [11]. Each issued document is automatically verified and approved by the relevant parties and is
permanently stored in a tamper-proof ledger on the blockchain, so its authenticity can be always
guaranteed.
As we see, most of these systems are oriented on the verification of documents and certificates,
which were issued by HEIs and other education organizations, and information about these
organizations (formal and statistical). But there is lack of information how HEIs could record
information about the learning process that leads to the diploma obtaining. As we mention above, to
confirm learning outcomes, competencies and skills of each student, HEI should take into account a
lot of information, which must be trustable and with the highest degree of protection against
counterfeiting.
For example, storing academic information in learning management systems (LMS) like Moodle
does not guarantee that there is no threat of data loss. Conversely, the exclusion of the users who
successfully passed the course or training leads to data removal in the system. And even if all
information is archived, there is no guarantee of the reliability of the data due to the fact that the
system administrator has full access to all data and can change it on the demand.
Since the method of storing data in the blockchain is devoid of these disadvantages, let's look at
examples of blockchain technology implementation in the education applications.
There are a number of ways for blockchain implementation in the education field, such as full
record of learning trajectory, trusted certification of learning results, decentralized sharing of
education resources, etc. The greatest advantage of this network is a decentralized peer-to-peer
infrastructure, supporting trust, accountability, transparency, identity management and openness.
In [12] a case study on the decentralization of lifelong learning using blockchain technology was
explored. In this case study, the Semantic Blockchain was used as a solution to combine all acquired
learning and accreditation experiences to form a holistic picture of a person's lifelong learning. The
purpose of this study is to offer transparent and permanent educational accreditation for learners
throughout their lives and to support them in their personal and professional progress.
In [13] blockchain technology was used to increase the flexibility of organization the student
activity and the results obtained via managing the attendance and the grades obtained by students.
Article [14] describes the problems of online education such as lack of results certification, poor
confidentiality and lack of an exchange mechanism. The authors combine blockchain technology with
online learning to address these challenges, creating a smart, decentralized and shared online
education system.
The article [15] describes research experiments on Smart Pedagogy with a lifelong learning
transcript called the passport of knowledge in blockchain architecture. The proposed scenario allows
students to publish proof of their academic achievement in blockchain-related formats for instant
authentication. The paper describes the experimental network, which consists of three nodes (located
in Latvia, in the USA and in Asia). Based on the proposed implementation, this approach validates
training evidence much better, eliminates passport fraud, and reduces organizational overhead for
stakeholders involved in verifying human knowledge documents.
The authors of the article "Blockchain, IoT and Fog Computing for Smart Education
Management" [16] presented a great summary of the literature review of these techniques and, based
on this review, applied modern technologies as an infrastructure for the development of educational
innovations. Blockchain is used for recording and storing various collaborative data based on
consensus in educational institutions, for developing teaching and learning on a digital platform, for
storing information about student history, educational history in different grades, registration
information, curriculum participation and institutional activities, academic performance and a
certificate of education [16]. The Internet of Things and Fog Computing are used to develop
infrastructure with the ability to create intelligent educational environments to support and quickly
answer questions about the use of all types of equipment for real-time control. They allow to organize
and share resources for collaboration work and training to gain access to the organization without
restrictions on time or place.
Thus, the usage of blockchain technology in education is widely discussing for the last 5 years in
the whole world, and in Ukraine particularly [17]. There is no doubt about the need to develop a
strategy for the digital transformation of university education [18] with the modernization of the
management of the corporate ecosystem, which should be implemented as a cloud platform. In this
article, it is planned to streamline the considered methods and approaches to address the issue of
creating an approach for saving intellectual and personal data involved in the training process in a
reliable storage protected from the possibility of forgery and unauthorized access.
3. An approach for intellectual property assurance in digital university
ecosystem
The process of transforming the educational environment in the format of "Smart
Environment" [19] and striving for the realization of the idea of "Smart Pedagogy" is a new trend in
the global educational field. Smart Pedagogy is a learning process in technology, different forms of
information and media-enriched environment. This led to the fact that there is a lot of digital
information which should be stored while the learning process in HEI and for a long time after its
completion (Figure 1).
Figure 1: Data for integration in the university digital infrastructure
In the university digital ecosystem, it is very important to have a proper process of collecting,
processing and storing the data about students’ educational results which could confirm the level of
the achieved outcomes within their study. The authors of the analyzed publications [12 - 17] agree
about the need of using the blockchain to provide a reliable information network.
The blockchain is a database made up of a series of fixed-length blocks ordered over time, which
could be integrated with applied information and communication technology in learning and teaching
processes [20]. Each block contains one or more confirmed transactions. After a block has been
verified and completed, it is added to the blockchain and all blocks are made public. The process of
adding a transaction consists of:
1. Adding a transaction to a block. On average, blocks contain approximately 1 MB of
information and are time stamped;
2. Cryptographic verification of each transaction;
3. Adding a new block after completion at the end of the block row, no transaction in the block
can be deleted or changed (unchangeable) (as shown at the Figure 2, adding a new block fixes the
hash of information from the previous block, which excludes the possibility of changing
information in the previous block in the future).
Figure 2: Blockchain structure
A Merkle root is a part of the block header and a simple mathematical way to verify the data on a
Merkle tree. Merkle trees are an essential part of blockchain technology. A Merkle tree is a structure
that allows for efficient and secure verification of content in a large body of data. This structure helps
verify the sequence and content of the data. A Merkle tree summarizes all the transactions in a block
by producing a digital fingerprint of the entire set of transactions, thus enabling a user to verify
whether or not a transaction is included in a block [21].
The Merkle tree will be created based on the decision about what data and in what form should be
stored in the blockchain.
Further consider the model for implementation of blockchain technology for intellectual property
assurance in the digital university ecosystem.
3.1. Intellectual property assurance method for digital university ecosystem
based on blockchain technology
Intellectual property assurance method for digital university ecosystem based on blockchain
technology consists of the following steps:
Step 1: Elicitation of the classes of the storing information. In this phase, all type of data
which should be stored in the blockchain should be identified and separated into public and
confidential.
Step 2: Deployment of files storing and implementation of data transferring process into a file
server.
Step 3: Selection of the method and keys for encrypting private information and files.
Step 4: Creating an interface system for uploading files and information into the blockchain
with the LMS integration.
Step 5: Storing information into the blockchain.
The first step is aimed to determine the information that needs to be stored to confirm the acquired
skills and educational level, as well as for the management of the student's learning process itself.
Upon admission, the applicant must provide a document on previously received education and its
supplementary, all required certificates, identity documents, a personal photo and other necessary
documents. These documents must be stored in an encrypted way during the entire educational
process, since contain confidential information.
After students are enrolled, the admission information is created – study degree, specialty/
educational program, form of study, type of financing, list of courses, etc. This information is public
and must be available without encryption to confirm the enrollment process. The document that
confirms this process is the enrollment order, a link to which can be attached to the enrollment record
(the document must be publicly available).
The training process generates the following set of files and data:
methodological support (should be publicly available with a link to authorship);
learning outcomes in the form of completed project and diploma thesis (should be publicly
available with a link to the owner), laboratory and practical work, reports, essays, etc. (must be in
private access with a link to authorship);
transcript of records – marks for all types of control and types of assignments (must be in
private access with a link to the student and teacher);
received learning outcomes (competencies and skills) (must be publicly available with a link
to the student);
student’s and teacher’s certificates and diplomas (should be publicly available with a link to
the owner).
In the second step, it is proposed to store the files on a backup server, where each file will be
assigned a unique number. Thus, a link to the file uploaded to the server will be saved in the
blockchain. Depending on the file type, it will be stored in its original or encrypted form.
To encrypt private files, in the third step a unique key should be chosen, ideally which will
uniquely identify the person who has access to this information. In each particular HEI, this key can
be selected based on their own preferences. As an example, in Ukrainian HEI it is proposed to use
identifiers from USEDE, i.e., person code in USEDE was chosen as the key for encrypting personal
data and documents and education code in USEDE was chosen as the key for encrypting learning data
and documents.
This choice depends on following factors:
until the student is enrolled, there is no education code, but there is already a need to preserve
the applicant's documents;
a person can study in several programs (at the same time or not) and thus the use of an
education code will allow separating this information, but at the same time personal information
will not be duplicated (it is tied to the person code in USEDE);
access to the person code and the training code has a limited circle of persons in the learning
process (university administration);
the graduate gets access to the education code (it is registered to the diploma supplement) for
further demonstration of the training outcomes to employers.
In step 4 should be realized the integration with the used training platform to avoid data
duplication and integrate the process of saving files and data into the blockchain without the need for
additional actions from the participants of the educational process.
In the fifth step information which was elicitation at the first step should be saved into blockchain.
3.2. Implementation of the blockchain for intellectual property assurance
method
A framework of the blockchain consist of the next layers, key ones of which will be described
below:
Data layer;
Network layer;
Consensus layer;
Incentive layer;
Contract layer;
Application layer.
3.2.1. Data layer
At the data layer storing information about data block, chain structure, timestamp, hash function,
Merkle tree and the encryption. The information shown in Figure 3 is entered into the blockchain
transaction. The proposed blockchain architecture consists of the transaction head and the transaction
data. The transaction data contains the nine columns where the data field carries information about the
education process, such as the Creator, Leaner (person code), Education id (can be null), BLOB data
(Smart Pedagogy Data), Transaction Type, File unique ID (from the file server), File hash (from the
file server via SHA-256 cryptographic hash function), Outcomes, Mark. And the transaction head
contains the four columns, such as the previous transaction key, the current transaction key, Merkle
root (hash) and Date of creation (timestamp).
Transaction Type can be one of:
Personal document (id = 1);
Education document (id = 2);
Intellectual property (learning outcome) (id = 3);
Mark for learning activity (competencies and skills) (id = 4).
Figure 3: Transaction structure
For producing a digital fingerprint of the transaction propose to use the hash of the next data
(Figure 4) using SHA-256 cryptographic hash function [22].
In the situation when the learner completed any activity for the second time, some documents
should be updated on the server or any information should be changed, and results which were
published in the blockchain before, this updated data will be uploaded and added into the blockchain
again. Then all other nodes would have both the previous and actual assessment values for the same
learner but with different timestamps (so the task of choosing the actual information will be the
easiest).
* can be null (0)
Figure 4: Merkle tree for learning information transaction
3.2.2. Consensus layer
The security of blockchain technology is achieved by the usage of the consensus algorithm. There
are different types of consensus algorithms that might be executed before inserting a transaction in a
block, comparison of which is presented in Table 1.
Based on the analysis of the advantage and disadvantages described in the Table I, the Delegated
Proof-of-Stake (DPoS) consensus algorithm was chosen. According to this algorithm, selected
delegates make the validation of the blocks by themselves. A relatively small number of delegates
(about a couple dozen) can organize themselves efficiently and create designed time slots to publish
blocks. With a collaborative effort and a partially centralized process, DPoS has been able to run
orders of magnitude which are faster than any other consensus algorithms [23]. Also disadvantage of
a partially centralized process in case of HEI’s blockchain organization become the advantage on
practice. Designing trusted delegates owned by the HEI as elected delegates will prevent a 51% attack
when an attacker or a group of attackers gain control of 51% or more of the computing power or hash
rate [24].
Table 1
Consensus algorithms comparison
Consensus Basis Disadvantages Advantages
algorithms name
Proof‐of‐Work Complex mathematical High CPU computations, Highly scalable
(PoW) calculations is energy‐intensive and
costly
Proof‐of‐Stake The PoS randomly selects Complex Higher speed, lesser
(PoS) validators, the higher implementations, energy consumption
chances of getting have vulnerable, only the and hardware
the most coin holders richest can have control requirements
of the consensus
Delegated Proof‐ Selected delegates make A partially centralized Offers all the
of‐Stake (DPoS) the validation process benefits of the PoS,
faster than any
other consensus
algorithms, secure
real‐time voting
Byzantine Fault Nodes regularly vote in There is no central High throughput,
Tolerance (BFT) order to identify the true authority that can step in cost‐efficiency,
transaction to correct it, low smart‐contract
scalability, semi‐ support
centralized system
Practical This computation process Susceptible to Sybil Forces a low
Byzantine Fault asks the individual attacks, does not scale overhead on the
Tolerance (PBFT), general about the opinion well performance of the
SIEVE on the message replicated service,
energy efficiency,
transaction finality,
low reward variance
Proof‐of‐Weight Mechanism gives users a Incentivization can be Energy efficient,
(PoW) 'weight' based on how hard highly customizable
much cryptocurrency and scalable
they are holding
Proof‐of‐Burn By committing coins to an The protocol wastes An interesting
(PoB) address where they are resources needlessly, alternative to Proof‐
irretrievable, user earns a mining power goes to of‐Work
lifetime privilege to mine those who are willing to
on the system based on a burn more money
random selection process
Proof of Authority An optimized Proof‐of‐ Strongly lack Low requirements
(PoA) Stake model that decentralization, the risk for computational
leverages identity as a of damaging the power, no
form of stake rather than reputation does not requirement for
actually staking tokens necessarily keeps a communication
person from participating between nodes in
in malicious actions order to reach
consensus, and the
continuity of the
network
3.2.3. Application layer
At the application level, the principle of interaction between applications and the blockchain is
described. The process of saving student project thesis with IP data in the blockchain is shown in
Figure 5.
Figure 5: An example of loading a project thesis into the blockchain of intellectual property of HEI's
participants
For application layer realization an interface system for uploading files and information into the
blockchain should be developed. One of the features of this system is the LMS integration and API
integration with the database with information about students and teachers. The LMS integration
should be used for a simple, protected and user-friendly process of data and files transfer. API
integration with the database is requested to obtain data about the student's person code and education
code. The specification for the development of this system will depend on the LMS used in HEI and
the access to the database with students' and teachers' information.
Taking into account the systems used in National University “Zaporizhzhia Polytechnic”, the
following application integration is planned (Figure 6). It should integrate information from the
university Moodle system, USEDE and data from the ECS eLearning Community Server, which is
supporting international projects ViMaCs: Virtual Master Cooperation Data
Science(ID: 57513461) [25] and Cross-domain competences for healthy and safe work in the 21st
century WOR4CE [26].
Figure 6: An example of the Application layer
4. Discussion
The proposed method can be used as a base for integration the data about students' educational
achieved outcomes within their study and IP. In line with the hypothesis that digital university
ecosystems are going to grow and expand the area of penetration, the application of this method can
be used for different purposes, affording transparency and secure data archiving into infrastructure.
The further implementation required integration of data from different sources so the cloud
infrastructure of the ecosystem is also of great importance.
5. Acknowledgements
This research was partly done within the framework of international project “Cross-domain
competences for healthy and safe work in the 21st century” (Ref. no. 619034-EPP-1-2020-1-UA-
EPPKA2-CBHE-JP).
6. Conclusions
Intellectual property assurance method for digital university ecosystem based on blockchain
technology was proposed in the article. The implementation of the proposed approach in different
HEIs could become the basis for creation of the global cloud platform for intellectual property. It
aimed to support the principles of academic integrity, afford transparency and secure archiving for
intellectual property into university digital infrastructure. Based on the data stored in the blockchain it
will be easy to confirm the presence of a diploma, learning competencies and skills, gained in the
educational process, particularly the results achieved within alternative disciplines, training,
internship as well as additional individual educational achievements.
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https://www.jumpstartmag.com/understanding-51-attacks-on-blockchains/
[25] ViMaCs: Virtual Master Cooperation Data Science URL: https://go-study-europe.de/vimacs/
[26] WORK4CE: Cross-domain competences for healthy and safe work in the 21st century. URL:
http://work4ce.eu/