=Paper=
{{Paper
|id=Vol-3646/Paper_14.pdf
|storemode=property
|title=The Development of the Information Technology Architecture for the Anonymisation of Stakeholders Personal Data of Digitalized Education based on Formulated Criteria and Requirements
|pdfUrl=https://ceur-ws.org/Vol-3646/Paper_14.pdf
|volume=Vol-3646
|authors=Iuliia Khlevna,Isus Raichuk,Oleksandr Timinskyi
|dblpUrl=https://dblp.org/rec/conf/iti2/KhlevnaRT23
}}
==The Development of the Information Technology Architecture for the Anonymisation of Stakeholders Personal Data of Digitalized Education based on Formulated Criteria and Requirements==
https://ceur-ws.org/Vol-3646/Paper_14.pdf
The Development of the Information Technology Architecture
for the Anonymisation of Stakeholders Personal Data of
Digitalized Education based on Formulated Criteria and
Requirements
Iuliia Khlevna, Isus Raichuk and Oleksandr Timinskyi
Taras Shevchenko National University of Kyiv, 60 Volodymyrska Street, Kyiv, 01033, Ukraine
Abstract
The article shows that currently, the question of protecting the personal data of stakeholders
in the digitalized educational sphere is important. The object of the research is the protection
processes of personalized data of stakeholders in the digitalized educational sphere. The
solved issue is a formalization of parameters and criteria when forming requirements for the
information system and the development of a concept for the architecture of information
technology based on which requirements for such kind of technology are justified. The
assessment of the degree of positive effect from the functioning of the information system
depending on the selected criteria is offered. Based on the completed formalization the
requirements to the architecture for information solution of anonymization of personal data in
the digitalization of education is defined; also, the requirements to the components of
architecture solution of information technology are formed. The architecture of information
technology on anonymization of personal data in the educational sphere is developed. The
characteristics of such a system are represented and they are evaluated as well. Well-
developed requirements and architecture are going to become the basis for the information
technology of anonymization of personal data of stakeholders of digitized education. The
prospects for further research are outlined.
Keywords 1
Digitalization, educational space, anonymization, architecture of information technology,
information system requirements, assessment of information system.
1. Introduction
In the era of great and fast development of digital technologies, virtualization and the growing
dependence from online resources the question of personal data protection become relevant as never
before. It mostly refers to the field of education, where digitalization is becoming necessary to ensure
access to knowledge at any time and from any place. However, along with this opportunity the threat
of violating the confidentiality of personal information of digital education stakeholders is rising. The
growing amount of data collected in educational institutions and platforms requires ensuring the
appropriate level of confidentiality and protection of personal information of students, teachers,
administration and other participants in the educational process.
Anonymization is a necessary tool that allows you to save valuable data for the analysis and
improvement of educational processes, while ensuring the anonymity and privacy of the persons
whose data is processed. In this regard, the development and application of information technologies
in the educational environment is a key aspect of the anonymization of personal data. At the same
time, it is worth to take into account that the main element in the formation of any information
technology is the formation of requirements for it. An urgent scientific task based on the above rises,
which consists of the development of the concept of the architecture of information technology, based
on which the requirements for such technology will be substantiated.
Information Technology and Implementation (IT&I-2023), November 20-21, 2023, Kyiv, Ukraine
EMAIL: yuliia.khlevna@knu.ua (Iuliia Khlevna); neversaydie.jr@gmail.com (Isus Raichuk); o.timinskyi@knu.ua (Oleksandr Timinskyi)
ORCID: 0000-0002-1874-1961 (Iuliia Khlevna); 0000-0002-0968-4811 (Isus Raichuk); 0000-0001-8265-6932 (Oleksandr Timinskyi)
©️ 2023 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)
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
139
2. Literature review
The accumulation of data, their processing, and the formation of decisions based on them is a
modern requirement, including in the educational sphere [1, 2]. The issue that scientists and
practitioners are addressing is the preservation of data confidentiality. In the digitized educational
space, the integration of data, and their aggregation from various sources for various educational and
scientific purposes is becoming increasingly widespread [3]. The responsibility for preserving the
confidentiality of the personal data of the stakeholders of the educational process remains open. It can
be argued that this is a task of legislation [4], but the question of how to protect this data is a question
of the institution that carries out educational activities.
The organizational processes of saving personal data in the digital space are reflected in [5-7]. The
disadvantage is that the formation of models, methods, and principles of confidentiality preservation
only with the use of organizational methods is not effective in the digital space. The continuation of
the research, in particular, the combination of anonymization operations, privacy models, and
presentation of some anonymization tools is presented in the article [8]. The disadvantage of the work
is that the work offers tools with ready-made solutions for data protection, with the involvement of
third-party platforms, which do not take into account the peculiarities of the activities of educational
institutions. Also, the use of external platforms that offer their own data protection is presented in the
work [9]. However, this protection may be outside the educational environment, which may conflict
with the requirements of the educational space. In works [10, 11] a solution was proposed using
information technology tools. The shortcoming of the works is that they do not single out the
requirements for information technologies of anonymization, and do not present an assessment of the
functioning of the information system of digitized education. The issue of anonymization of
information extraction and automatic display of confidential documents is presented in the work [12].
The disadvantage is that the information system can process a limited type of data. Recently, the use
of artificial intelligence tools for saving conference information has become particularly widespread
[13-15]. The disadvantage of this method for implementation in the educational field is that data is
required for training systems, and artificial intelligence requires access to information transmitters,
storage, etc. It is appropriate for educational institutions to develop information technology in which
the main focus will be on the source of data in the middle of the educational environment.
Therefore, the analysis of the resources has shown that the research aimed at solving issues related
to the formalization of the anonymization of personal data of stakeholders in the digitalized
educational sphere and the formation of the concept of requirements for the information technology of
the anonymization of personal data and the formation of its technological solutions is promising.
3. Purpose and objectives of the research
The purpose of the research is to develop an information technology architecture for the
anonymization of personal data of stakeholders in the digitized educational sphere based on the
formalization of parameters, needs and requirements for the information system which will make it
possible to develop protection of confidentiality, integrity and availability of data in the conditions of
digitization of the educational sphere with the use of information technologies.
To achieve this goal, the following tasks must be solved:
to propose indicators and criteria reflecting the degree of positive effect from the functioning of
the information system of anonymization of personal information in the digitized educational sphere;
to form requirements for the architecture of the information solution for personal information
anonymization in the digitized educational sphere;
to develop the architecture of the information system of personal data anonymization.
4. Indicators and criteria reflecting the degree of positive effect from the
information system functioning of personal information anonymization
The growing volume of data accumulated in the digital Eco space of education is a prerequisite for
the formalization of indicators of personal data anonymization in relation to its stakeholders. A
classification of indicators and criteria for anonymization of stakeholder’s personal data in the
digitized educational sphere is proposed (Table 1). The main condition of the classification is the
validity of the indicators and criteria of anonymization of personal information in the digitized
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educational sphere, which reflect the degree of positive effect from the functioning of the information
system.
Table 1
Formalization of indicators and criteria that reflect the degree of positive effect from the
information system functioning of personal information anonymization in the digitized educational
sphere
The validity of the need for effective Indi-
Classification
anonymization in the conditions of Criteria cati-
index
digitized education on
Reducing the risk of stakeholder data
Pr
leakage
With the increasing use of digital Keeping data useful Pс
platforms and tools in education, Data access control Pа
students, teachers, parents and other Context preservation Pk
stakeholders are disclosing a Ensuring the System performance Pо
significant amount of personal privacy of Reliability of the anonymization
Pre
information. Anonymization allows stakeholders (PS) method
you to protect this data from Scalability Ps
unscrupulous persons and avoid Flexibility Pf
possible misuse of this information Protection against discrimination of
Pd
educational process stakeholders
Economy of anonymization Pe
Legislation on the protection of
personal data (for example, GDPR [16])
sets strict requirements for the
processing of personal information. Compliance with
Anonymization allows educational legislative S
institutions to meet these regulations (S)
requirements without burdening the
analysis and use of data to improve
processes
Validity of processing Ар
Balanced Analysis and tracking of changes Ас
analytics of Work with different types of data Аt
anonymization of Deanonymization of data within the
personal data of local information network of the Аd
Anonymization of personal data allows stakeholders in educational institution
for analysis and research without the digitized Integration of anonymized system Аі
risking the disclosure of identifying educational The validity of the accumulation,
information. This promotes a healthy sphere (A) processing and transmission of Аdm
balance between collecting valuable information
data to improve the educational Increasing the
process and preserving user privacy confidence of
stakeholders Distribution of anonymized data only
regarding the with authorized external consumers Аа
protection of of personal information
their personal
data
The carried-out formalization, according to the presented parameters and criteria, became the basis
for determining proposals for the development of requirements for the technology of anonymization
of personal data of stakeholders of digital education. In particular, on the basis of the formalization
carried out, the requirements for the architecture of the information solution for the anonymization of
personal information in the digitized educational sphere were formed:
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1. Full anonymization – the system must ensure that no personally identifiable information can be
recovered from anonymized data. This ensures that information remains confidential and private.
2. Preservation of the usefulness of data - during anonymization, it is important to preserve the
value of data for further analysis and research. Data must remain sufficiently representative and useful
to provide holistic insight without the risk of identity disclosure.
3. Specialized anonymization algorithms – the use of appropriate anonymization algorithms is key
to ensuring a high level of privacy. These algorithms may include data substitution, encryption, and
masking techniques.
4. Access control – the system must have a thorough access control mechanism that allows
restricting access to anonymized data only to authorized users with the appropriate authority.
5. Data encryption – to prevent possible unauthorized access to anonymized data, it is important
to use strong encryption at the level of data storage and transmission.
6. Preservation of context – the system must preserve some level of context to ensure the validity
and usefulness of the data. This helps to correctly interpret and analyze anonymized data.
7. Monitoring and auditing – it is important to conduct constant monitoring and auditing of the
anonymization system in order to identify possible privacy violations and eliminate them in a timely
manner.
8. Ease of integration with the existing ecosystem – the personal data anonymization system
should be developed taking into account the ease of its integration into the existing information and
technological infrastructure of the educational institution. This allows you to reduce efforts and risks
when implementing a new system, while keeping the work of other components of the ecosystem
unchanged. Ease of installation and use facilitates faster and more efficient implementation of
personal data anonymization, ensuring a smooth transition to a new level of data protection in a
digitized educational environment.
9. In addition, the information system of personal data anonymization should possess such
properties as: scalability, flexibility, speed of processing, combination of anonymization methods.
The degree of the positive effect of the functioning of the information system of anonymization of
personal data in the digitized educational space is proposed to be evaluated by:
𝑃𝑟 ⇒ 𝑚𝑖𝑛, 𝑃𝑐 ⇒ 𝑚𝑎𝑥, 𝑃𝑎 ⇒ 𝑚𝑎𝑥, 𝑃𝑘 ⇒ 𝑚𝑎𝑥, 𝑃𝑜 ⇒ 𝑚𝑎𝑥,
𝑃𝑟 ⇒ 𝑚𝑎𝑥, 𝑃𝑠 ⇒ 𝑚𝑎𝑥, 𝑃𝑓 ⇒ 𝑚𝑎𝑥, 𝑃𝑑 ⇒ 𝑚𝑎𝑥, 𝑃𝑒 ⇒ 𝑚𝑖𝑛,
𝑆 ⇒ 𝑚𝑎𝑥, (1)
𝐴𝑝 ⇒ 𝑚𝑎𝑥, 𝐴𝑐 ⇒ 𝑚𝑎𝑥, 𝐴𝑡 ⇒ 𝑚𝑎𝑥, 𝐴𝑑 ⇒ 𝑚𝑎𝑥,
𝐴𝑖 ⇒ 𝑚𝑎𝑥, 𝐴𝑑𝑚 ⇒ 𝑚𝑎𝑥, 𝐴𝑎 ⇒ 𝑚𝑎𝑥.
{ }
If there is no information technology in the educational environment that meets the specified
requirements, anonymization can be estimated with some integrated value a-, and with the use of
information technology that meets the established requirements - value a+, and at the same time, the
anonymization value is much higher than before the use of the information system, which meets the
stated requirements (а+>>а-), then we can say that the developed information system is effective.
Anonymization is justified. We believe that meeting these requirements will help create an effective
personal data anonymization system that ensures a high level of confidentiality and privacy protection
for participants in the digitalized educational sphere.
5. Development of the information system architecture of personal data
anonymization
The modular architecture of the personal data anonymization information system, which meets the
established requirements, is presented in fig. 1. The main components of the proposed information
system are: the information management system of the educational institution, the interconnection of
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various information systems of the educational institution (integration layer), the system of
anonymization of personal data of stakeholders of the digitized educational sphere.
Figure 1: Architecture of information technology of personal data anonymization
1. Educational institution information management system (Education institution information
management system) - the existing centralized digital system for managing all information of the
educational institution with which the future integration of the personal data anonymization system
will take place. The following structure of this block is proposed:
The database of the educational institution (EI DB) is a digital repository of all the information
necessary for the full functioning of the educational institution.
The data access layer (DAO) is a specific implementation of the mechanism for providing read
and write operations to the database.
The business logic layer (Service) is a management layer that provides all the necessary
functions for manipulating the data structure of an educational institution.
Data access management service of the educational institution is one of the most important
elements of the system, a layer that provides authorized access to the data of the educational
institution.
The controller layer (Controllers) is a layer that provides and declares ways of obtaining and
manipulating information.
The admin panel of the educational institution (EI Admin UI) is a tool for managing the digital
information of the educational institution by appropriately trained personnel.
2. Integration layer – a layer that ensures internal communication of various information systems
of an educational institution. In the context of integration with the personal data anonymization
system, this layer ensures the distribution of personal data to the anonymization system, respectively,
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for their further anonymization by this system. The flow of new data (reports, assessments, etc.)
obtained from external sources will go in the opposite direction.
3. Information system of anonymization of personal data of stakeholders of the digitized
educational sphere (Anonymization system) - a system whose purpose is to integrate into the existing
digital data management tools of the educational institution is to ensure a high level of protection of
personal data of stakeholders of the educational process. The architectural components of the personal
information anonymization system are as follows:
The database of the anonymization system (API DB) is a repository for saving generated
anonymous data and all metadata necessary for their internal identification and processing.
The layer of access to the database of the anonymization system (Anonymization DAO) is a
layer that provides access to the information of the database of the anonymization system and
provides tools for working with it.
The business logic layer of the anonymization system (Anonymization Service) is a layer in
which real data is processed, their anonymous substitute copies are generated, identifiers are de-
anonymized, and other business logic is related to the anonymization and de-anonymization of
personal information.
Anonymization Data API – an interface that provides an authorized exchange of information
between an educational institution and external educational platforms used by stakeholders of the
educational ecosystem to ensure the effectiveness of the educational process.
The main characteristics of the information technology of personal data anonymization have been
determined, from the point of view of ease of use and efficiency of performance of the functions
assigned to the system. Such indicators are often decisive when integrating new functional units into
the existing information technology. The characteristics of the proposed architecture of the
anonymization system are:
1) Scalability (Ps) such an architecture is able to effectively scale with respect to the growing
amount of data accumulated in the educational process. After all, the use of a separate layer of access
to the database allows, by modifying only it, to switch to different models of data storage, such as
distributed databases. This will ensure reliable operation of the system even with an increase in the
volume of information.
2) Flexibility (Pf): such an architecture can be adapted to different types of data that are
processed in an educational context. After all, the data types of the anonymized database essentially
repeat the already existing data types (tables) in the database of the educational institution.
3) Various methods of anonymization (Adm) having the logic of anonymization in a separate
layer (Anonymization Service) modification of the only particle will allow to support various methods
of anonymization, including substitution, general encryption, hashing and others. This allows you to
choose the best approach for a specific type of data and specific privacy requirements.
4) Integration with existing systems (Ai): such a modular, separate architecture of the
anonymization system can be compatible with various existing information systems and platforms of
the educational institution. After all, it does not require changes to the existing digital data
management system of the educational institution, but is a separate addition. That is, it is enough to
simply configure the integration layer of messaging between the existing data management system
and the anonymization system of users' personal information. This approach ensures convenient and
smooth implementation of the future data anonymization system.
5) Processing Speed (Po): This approach (separate system) is efficient in terms of data
processing speed. After all, the system is able to provide timely anonymization with minimal impact
on the productivity of the entire digital management system of the educational institution.
These are characteristics that together create a simple, reliable and effective architecture of the
system of anonymization of personal data of stakeholders in the digitized educational sphere, ensuring
reliable protection of the confidentiality and privacy of participants in the educational process and
reflecting the extent of the positive effect of the functioning of the information system in the digitized
educational space.
When forming the architectural vision of the information system for the anonymization of personal
data of stakeholders in the digitized educational sphere, the next step was the formation of
144
requirements for the components of the architectural solution of the information technology of
personal data anonymization. The following requirements are proposed for:
Databases of the anonymization system:
1. The database must use strong encryption for data storage and transmission.
2. Regular data backup helps ensure recovery of information in case of possible data loss.
3. Ability to track and store different versions of anonymized data, which allows analysis and
tracking of changes.
4. Different types of data and ways of processing them to meet the different needs of the
educational field.
5. Large volumes of data in the educational field require high speed of processing and queries to
the database.
6. The ability to audit user actions in the database helps identify and respond to potential security
threats.
Layer of access to the database of the anonymization system:
1. The layer should include measures to protect against SQL injection attacks, which can be used
by attackers to gain access to the database.
2. The implementation of the toolkit should be based on current information technologies to
ensure the maximum level of speed and data protection.
3. A mandatory requirement is the possibility of asynchronous transactional work with the
database.
4. Speed of data return is a key goal.
The business logic layer of the anonymization system:
1. The service layer should be ready for integration with existing systems of educational
institutions, ensuring convenient and joint work with data.
2. The service layer should provide the ability to process user requests for anonymized data and
ensure their integrity.
3. The system should be able to manage the anonymization process, including the choice of
methods, parameters and saving mappings for possible data recovery (provided that this does not
violate confidentiality).
4. The service layer should ensure the implementation of various data anonymization methods,
such as substitution, encryption, hashing, and others.
Data access interface by external consumers:
1. The data access interface (DIA) must use authentication mechanisms to verify the identity of
external consumers and authorization systems to control their level of access to anonymized data.
2. The interaction between external consumers and the system should take place using secure data
transfer protocols, such as HTTPS, to ensure data privacy and security.
3. The API must have clear and understandable documentation that explains functionality, request
and response parameters, and interaction rules.
4. The API must provide the ability to restrict access to certain types of data or certain operations
in accordance with user access rights.
5. To provide additional security, it is possible to implement authentication using API keys or
tokens.
6. The API must provide stability and unbroken interoperability for external consumers, ensuring
that changes to the API do not break existing functionality.
7. The access interface should include protection measures against possible attacks, such as brute
force attacks, injections, and others.
8. Ability to use mechanisms for limiting the number of requests from one consumer to prevent
system overload.
9. The API should be able to track and log the activity of external consumers for analysis and
monitoring.
It was determined that the anonymized data base of the system and the data access interface
deserve special attention. Researching the API layer is not very cost-effective, because there are many
standards for building APIs of various systems (such as REST, SOAP, etc.), as well as authorization
standards (OAuth, OpenID, etc.). Speaking of DBMS implementations, there is also something to
145
choose from here, but considering the importance of this block, it is worth developing the database
structure of the information technology of personal data anonymization in accordance with the
established requirements.
6. Scheme of the information technology database of personal data
anonymization
A fragment of the generalized scheme of the relational database is presented in fig. 2.
Figure 2: Database scheme of the personal information anonymization system
Basically, this scheme consists of two parts. Table-register of consumers of personal information
(data_suppliers) - a list of existing consumers of personal data of the educational edition with their
unique identifier (s_sd). The set of fields of such a table depends on the necessary information of the
educational institution about a certain data consumer.
𝑛
𝑆𝐹 = ∑ 𝐹 = 𝑠𝑓1 + 𝑠𝑓2 + ⋯ + 𝑠𝑓𝑛 (2)
𝑖=1
Where SF – a set of fields of the table of consumers of personal information, F and sf – a certain
field of such a table, n is the number of all fields of the table. A set of tables for each type of data for
each consumer (s_id + entity_type) is a set of tables (AT) for storing anonymized instances of each
type of data of an educational institution for each consumer of such data separately.
𝑛 𝑚 𝑛 𝑚
∑ 𝐸 = 𝐸1 + 𝐸2 + ⋯ + 𝐸𝑛 ∑ 𝑆 = 𝑆1 + 𝑆2 + ⋯ + 𝑆𝑚 𝐴𝑇 = ∑ 𝐸 ∗ ∑ 𝑆 (3)
𝑖=1 𝑖=1 𝑖=1 𝑖=1
Where E is a certain type of data stored by the educational institution, n is the number of such
types; S is a specific user of educational institution data, m is the number of such users. AT is the final
set of tables. The set of fields of such tables will contain all the same fields that contain real tables of
each type, as well as an additional identifier (e_id). That is, the list of fields of such a table can be
expressed as follows:
𝑛 𝑛
∑ 𝐸𝐹 = 𝐸𝐹1 + 𝐸𝐹2 + ⋯ + 𝐸𝐹𝑛 𝐸𝑆𝐹 = ∑ 𝐸𝐹 + 𝑒𝑖𝑑 (4)
𝑖=1 𝑖=1
146
Where EF is a set of database table fields of a certain type stored by an educational institution, n is
the number of such fields in the educational institution's table; ESF - a set of table fields of the
anonymization service database of a certain type of data stored by the educational institution; e_id is a
field for storing the identifier of a certain table. As a result, we get the following features of such an
anonymous database table scheme. First of all, the more the integrated educational institution with the
greater number of consumers of anonymous data, the greater the number of tables we will have in the
database scheme. Secondly, the more different types of personal data the educational institution
stores, the more tables of anonymous versions of them the scheme of the anonymous data base will
have. Therefore, we’ve got such a conclusion:
𝑃𝑠 ⇒ 𝑚𝑎𝑥 (5)
That is, it is possible to increase the number of tables in the scheme of the anonymous data base of
the educational institution. But for modern DBMS, thousands or even hundreds of thousands of tables
do not cause any problems.
𝑃 ⇒ 𝑚𝑎𝑥, 𝐴 ⇒ 𝑚𝑎𝑥, 𝐴 ⇒ 𝑚𝑎𝑥, 𝐴 ⇒ 𝑚𝑎𝑥. (6)
о 𝑐 𝑡 𝑑𝑚
We have a separate set of tables for each consumer, that is, a separate table for each type of data.
Hence, parallel work with data for each individual type of data of each individual consumer does not
in any way affect the consistency of data of other users, as well as the speed of processing requests of
other data consumers. Which, as stated earlier, is a key requirement for the system of anonymization
of personal information of stakeholders of a digitized educational institution.
7. Conclusions
The article has formalized indicators and criteria that reflect the degree of positive effect from the
functioning of the information system of anonymization of personal information of stakeholders in the
digitized educational sphere. The indicators are: ensuring the privacy of stakeholders, compliance
with legal regulations, balanced analytics of anonymization of personal data of stakeholders in the
digitalized educational sphere, and increasing the trust of stakeholders regarding the protection of
their personal data. Criteria are given for each indicator. An assessment of the degree of positive
effect of the functioning of the information system is proposed, depending on the selected criteria.
The carried-out formalization became the basis for determining the requirements for the architectural
component of the anonymization of the personal data of stakeholders.
The requirements for the architecture of the information solution for the anonymization of personal
information in the digitized educational sphere have been determined, and the requirements for the
components of the information technology architectural solution have also been formed. It was
established that the database of anonymized data of the system deserves special attention when
forming requirements. The architecture of the information technology solution for the anonymization
of personal data in the field of education has been developed. The main features of the obtained
solution are described. The database scheme in the environment of the information technology
architecture of anonymization of personal information of stakeholders of the digitized educational
sphere has been developed and described in detail. An algorithm for its formation is also proposed,
taking into account the specifics of the educational institution's data scheme.
Further research in this direction is planned to be focused on the detailed selection of technologies
and standards for the implementation of the system of anonymization of personal information of
stakeholders of a digitized educational institution based on the developed architecture. As well as
further implementation of the anonymization system itself and its integration into the educational
institution.
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