Development of decision support system using OLAP-technologies for information security monitoring systems
The article highlighted the need for continuous monitoring of the computer networks (CN) for information security and analyzed the sources of data for information security monitoring (ISM). Methods of data collection from various sources have been investigated, and categories of ISM systems have bee...
Saved in:
| Date: | 2023 |
|---|---|
| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
PROBLEMS IN PROGRAMMING
2023
|
| Subjects: | |
| Online Access: | https://pp.isofts.kiev.ua/index.php/ojs1/article/view/541 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Journal Title: | Problems in programming |
| Download file: |  |
Institution
Problems in programming| _version_ | 1859510319040167936 |
|---|---|
| author | Dashdamirova, K.Q. |
| author_facet | Dashdamirova, K.Q. |
| author_sort | Dashdamirova, K.Q. |
| baseUrl_str | https://pp.isofts.kiev.ua/index.php/ojs1/oai |
| collection | OJS |
| datestamp_date | 2023-06-25T08:02:24Z |
| description | The article highlighted the need for continuous monitoring of the computer networks (CN) for information security and analyzed the sources of data for information security monitoring (ISM). Methods of data collection from various sources have been investigated, and categories of ISM systems have been studied. The architectural-technological model of the system supporting decision-making based on OLAP (Online Analytical Processing) and data warehouse has been proposed for quick response to security-related incidents and detected incidents in ISM systems.Prombles in programming 2022; 3-4: 403-408 |
| first_indexed | 2025-07-17T09:41:21Z |
| format | Article |
| fulltext |
403
Захист інформації
УДК 681.3 http://doi.org/10.15407/pp2022.03-04.403
DEVELOPMENT OF DECISION SUPPORT SYSTEM
USING OLAP-TECHNOLOGIES FOR INFORMATION
SECURITY MONITORING SYSTEMS
Konul Dashdamirova
У статті висвітлено необхідність постійного моніторингу комп’ютерних мереж з метою забезпечення інформаційної безпеки та
проаналізовано джерела даних для моніторингу інформаційної безпеки . Досліджено методи збору даних з різних джерел, до-
сліджено категорії систем моніторингу інформаційної безпеки. Запропоновано архітектурно-технологічну модель системи під-
тримки прийняття рішень на основі OLAP (Online Analytical Processing) і сховища даних для швидкого реагування на інциденти
безпеки та виявлені інциденти в системах моніторингу інформаційної безпеки.
Ключові слова: інформаційна безпека, моніторинг інформаційної безпеки, SIEM, UBA, OLAP, сховище даних
The article highlighted the need for continuous monitoring of the computer networks (CN) for information security and analyzed the
sources of data for information security monitoring (ISM). Methods of data collection from various sources have been investigated, and
categories of ISM systems have been studied. The architectural-technological model of the system supporting decision-making based on
OLAP (Online Analytical Processing) and data warehouse has been proposed for quick response to security-related incidents and detected
incidents in ISM systems.
Keywords: Information Security, Information Security Monitoring, SIEM, UBA, OLAP, Data warehouse
Introduction
The rapid development of the global Internet network and Information Communication Technology (ICT)
has led to the formation of an information environment that affects all spheres of human activity. The emergence
of local and global CNs facilitated the rapid dissemination of information and created new opportunities for
information exchange. New technologies increase the efficiency of production processes and contribute to the
expansion of business relations. However, despite the intensive development of ICT, the vulnerability of modern
information systems and the CN does not decrease, and the dependence of the information technologies used by
society on the degree of security is increasing. Modern methods of processing, transmission and collection of
information lead to the emergence of threats related to the loss, distortion and disclosure of information. The CN
is constantly exposed to various types of cyber threats. These threats can be hacker attacks, malicious programs,
outdated or faulty network equipment and operating systems, mobile and public cloud computing, third-party
service providers, and so on [1]. In an environment where cyber threats are widespread and unavoidable, rapid
detection of cyber threats and rapid response to possible incidents are of great importance to ensure the uninter-
rupted and reliable operation of the CN. The need for continuous monitoring of the information security of the
CN becomes urgent. ISM is the process of collecting, systematizing and analyzing information about the status
of the network and the behavior of its users [2]. Modern ISM systems operate in a continuous, automatic mode,
allowing timely detection of threats and the preparation of appropriate notifications. Serves to prevent security
risks promptly.
Analysis of sources on which ISM systems are based
Information security is monitored by the process of checking all security incidents obtained from various
sources. The source of incidents can be CERTs, antivirus systems located in the infrastructure of various organiza-
tions, operating system logs, scanners for security analysis of information infrastructure, network equipment, and other
sources (Fig. 1.) [3].
Інформаційні системи
© K.Q. Dashdamirova, 2022
ISSN 1727-4907. Проблеми програмування. 2022. №3-4. Спеціальний випуск
УДК 681.3 http://doi.org/10.15407/pp2022.03-04...
DEVELOPMENT OF DECISION SUPPORT SYSTEM USING OLAP-
TECHNOLOGIES FOR INFORMATION SECURITY MONITORING
SYSTEMS
Konul Dashdamirova
У статті висвітлено необхідність постійного моніторингу комп'ютерних мереж з метою забезпечення інформаційної безпеки та
проаналізовано джерела даних для моніторингу інформаційної безпеки. Досліджено методи збору даних з різних джерел, дослі-
джено категорії систем моніторингу інформаційної безпеки. Запропоновано архітектурно-технологічну модель системи підтримки
прийняття рішень на основі OLAP (Online Analytical Processing) і сховища даних для швидкого реагування на інциденти безпеки та
виявлені інциденти в системах моніторингу інформаційної безпеки.
Ключові слова: інформаційна безпека, моніторинг інформаційної безпеки, SIEM, UBA, OLAP, сховище даних
The article highlighted the need for continuous monitoring of the computer networks (CN) for information security and analyzed the sources
of data for information security monitoring (ISM). Methods of data collection from various sources have been investigated, and categories of
ISM systems have been studied. The architectural-technological model of the system supporting decision-making based on OLAP (Online
Analytical Processing) and data warehouse has been proposed for quick response to security-related incidents and detected incidents in ISM
systems.
Keywords: Information Security, Information Security Monitoring, SIEM, UBA, OLAP, Data warehouse
Introduction
The rapid development of the global Internet network and Information Communication Technology (ICT) has
led to the formation of an information environment that affects all spheres of human activity. The emergence of local
and global CNs facilitated the rapid dissemination of information and created new opportunities for information
exchange. New technologies increase the efficiency of production processes and contribute to the expansion of business
relations. However, despite the intensive development of ICT, the vulnerability of modern information systems and the
CN does not decrease, and the dependence of the information technologies used by society on the degree of security is
increasing. Modern methods of processing, transmission and collection of information lead to the emergence of threats
related to the loss, distortion and disclosure of information. The CN is constantly exposed to various types of cyber
threats. These threats can be hacker attacks, malicious programs, outdated or faulty network equipment and operating
systems, mobile and public cloud computing, third-party service providers, and so on [1]. In an environment where
cyber threats are widespread and unavoidable, rapid detection of cyber threats and rapid response to possible incidents
are of great importance to ensure the uninterrupted and reliable operation of the CN. The need for continuous
monitoring of the information security of the CN becomes urgent. ISM is the process of collecting, systematizing and
analyzing information about the status of the network and the behavior of its users [2]. Modern ISM systems operate in
a continuous, automatic mode, allowing timely detection of threats and the preparation of appropriate notifications.
Serves to prevent security risks promptly.
Analysis of sources on which ISM systems are based
Information security is monitored by the process of checking all security incidents obtained from various
sources. The source of incidents can be CERTs, antivirus systems located in the infrastructure of various organizations,
operating system logs, scanners for security analysis of information infrastructure, network equipment, and other
sources (Fig. 1.) [3].
Fig. 1. Sources for information security monitoring
CERT (Computer Emergency Response Team) is a group of computer security experts involved in collecting,
monitoring, classifying, and neutralizing incident information. The main purpose of CERT is to analyze incidents sent
by users (phishing, social engineering), suspicious files, viruses, as well as network traffic sessions, to respond quickly
to new threats, inform users and develop security recommendations [4].
СERT Antivirus
systems OS logs Security
scanners
Network
equipment
Fig. 1. Sources for information security monitoring
CERT (Computer Emergency Response Team) is a group of computer security experts involved in collecting,
monitoring, classifying, and neutralizing incident information. The main purpose of CERT is to analyze incidents sent
© К. Дашдамірова, 2022
ISSN 1727-4907. Проблеми програмування. 2022. № 3-4. Спеціальний випуск
404
Захист інформації
by users (phishing, social engineering), suspicious files, viruses, as well as network traffic sessions, to respond quickly
to new threats, inform users and develop security recommendations [4].
The first CERT group was formed at Carnegie Mellon University in 1988 after thousands of servers were
infected with the Morris worm. The group currently has the status of a CERT coordination center and licenses and
coordinates the activities of information security incident response centers around the world. National, regional or
industrial CERTs can be established in coordination with Carnegie Mellon University. Currently, many companies
around the world also create CERTs, but not all of them receive official status [5]. In total, there exist currently about
250 CERT teams in various countries around the world. Analysis of data collected in CERTs can allow for the timely
detection and prevention of cyber threats and the assessment of the level of information security within a country to
ensure the social security of society.
Today, computer viruses and malware are a real source of danger for any enterprise, organization, and others
that use information technology in their activities. The widespread use of these global networks can be explained by the
insufficient attention to network security issues in a large number of local computer networks. Computers are increasingly
infected with malicious software when working with Internet resources or through email messages. The target of viruses
can be any user’s computer, global or local computer networks. The damage can lead to the failure of the computer and
all computer networks in general, the violation of data integrity, accessibility, and confidentiality.
Every year, the creation of new types of viruses that can bypass traditional protection methods raises the issue
of protecting computer networks from malware. An important way to fight computer viruses is to prevent them in time.
Timely detection of infected files or disks, and complete destruction of detected viruses on each computer help to prevent
the spread of the virus epidemic to other computers and computer networks. Antivirus software is a special program that
is used to detect computer viruses, as well as undesirable (considered harmful) programs, recover infected (modified) files
by these programs, and prevent infection (modification) of files or operating systems with malicious code. Network anti-
virus programs carry out monitoring of servers, network computers, and installed software, allow you to monitor e-mail,
data of allowed network protocols (HTTP, FTP), file servers, external carriers (floppy disks, flashcards, CDs, DVDs), as
well as all channels through which computer viruses and malicious programs can penetrate [6].
The essence of the antivirus monitoring method is that the antivirus program is constantly in the computer’s
memory and monitors all suspicious actions performed by other programs. Antivirus monitoring allows you to check
all running programs, created, opened, and saved documents, programs, and files received via the Internet. The antivi-
rus monitor will inform the user if any program tries to perform potentially dangerous actions.
Log files found in the logs of operating systems or web servers contain system information about the operation
of the server or computer and information about the user behavior. The purpose of log files is to record all operations
performed on the webserver or computer for monitoring by the administrator. This information is of great importance
in the event of security incidents. Regular monitoring of logs and analysis of log files allows to identify errors in the
operation of a particular system or site, diagnose malicious activity, identify threats, threats, collect information about
user behavior, as well as evaluate according to various criteria [7].
Weaknesses in information systems, infrastructure nodes, and elements of the information security complex cre-
ate great problems for information security. To identify vulnerabilities, companies need to analyze the security of their
information infrastructure. As a rule, vulnerability scanners are used for security analysis from automatic instruments
operating in static and dynamic scanning modes. At present, this class of tools allows you to solve a wide range of prob-
lems. A vulnerability scanner is a program that identifies and creates a registry of all systems connected to the network
(servers, computers, virtual machines, containers, firewalls, switches, and printers). The program allows you to identify
each device, the operating system and installed programs on this device, as well as other attributes such as open ports
and user accounts and passwords, as well as track other elements that pose a potential threat to information security [8].
Faults in the hardware or software of the CN, slowing down or stopping the operation of important network services
can lead to unpleasant consequences. A modern network equipment monitoring system is a complex information system that
monitors servers, hosting, processes, and services on users’ computers, as well as files, folders, and databases. It consists of
the following components.
̶ network device indicators (CPU, temperature, device availability, packet loss, interface errors, available
throughput, etc.) are critical parameters that need to be monitored;
̶ monitoring – the process of collecting, assembling, and analyzing indicators to improve the understanding
of the characteristics and behavior of the components of the system. The data collected as a result of the
monitoring can be visualized and drawn in the form of various graphs, diagrams, and histograms.
̶ the warning system is an important component that takes action when changes occur in the values of the
observed indicators. When the critical value is reached, the metric value can try to solve the problem itself ac-
cording to the developed scenario or send an alert to the responsible person using SMS, email, and so on [1, 2].
The network equipment monitoring system allows receiving timely information about the fault, controlling the
situation, to eliminate the fault with minimal time loss [10]. During ISM, the monitoring information can be collected
from various sources using both automated and non-automated tools. Primary data collection is used to analyze the
state of information security and conduct various types of assessments. The following methods can be applied to obtain
primary data during the use of automated monitoring tools (Fig. 2):
̶ agent-based data collection (agents for security incident monitoring);
̶ data collection without agent;
̶ questionnaires (forms);
̶ software.
405
Захист інформації
Інформаційні системи
̶ questionnaires (forms);
̶ software.
Fig. 2. Methods for collecting information from different sources
A security monitoring agent is software installed on information infrastructure components and information
system nodes to gather the necessary information directly from a source. Monitoring agents can be used to collect
information on security incidents, software effectiveness, user behavior, and other information.
The method of collecting data without agents involves the receipt of data from sources over the network without
installing additional software for monitoring. Non-Agent data collection methods include:
̶ Read data directly from security log files or databases;
̶ Receiving information from sources using standard protocols for transmitting information about security
events;
̶ Data collection by connecting to the program interface or the web service of the data source.
By the usage of agent-free data collection method, data collection can be carried out about security incidents, the
operability of the software, and other information that the source can provide.
The collection of data on security incidents using questionnaires (forms) is carried out by filling in special
electronic (paper) forms and then transferring them to information security monitoring personnel.
Data collection method using software includes information management systems on information security
threats, security control systems, inventory means of software and technical means, software and information protection
tools, and so on [10].
Categories of ISM systems
All currently established and used ISM Systems can fall into one of the following categories.
SIEM (Security Information and Event Management) is a system that allows analyzing data obtained from
various sources in real-time. SIEM is a combination of Information Security Management and security event
management systems into a single security management system. The results of the analysis carried out by SIEM are
presented in a single interface, accessible to security analysts. This also facilitates the study of the corresponding
characteristic features of security events and allows analyzing the events that occur in order to respond to security
threats in real-time (Fig. 3). Sources of information for SIEM systems can be antivirus programs, authorization and
authentication systems, network screens, security walls, logs of network equipment, servers and workstations, intrusion
detection and prevention systems (IDS / IPS), information leakage prevention systems (DLP) and other programs [11].
Agent based Without agent Questionnaires
(forms) Software
Log Analysis
Log Collection
Event Correlation
Log Forensics
IT Compliance
App Log Monitoring
Object Access Auditing
Real-Time
User Activity Monitoring
Dashboards
Reporting
File Integrity Monitoring
Sistem & Device Log
Monitoring
Log Retention
SIEM
Fig. 2. Methods for collecting information from different sources
A security monitoring agent is software installed on information infrastructure components and information
system nodes to gather the necessary information directly from a source. Monitoring agents can be used to collect in-
formation on security incidents, software effectiveness, user behavior, and other information.
The method of collecting data without agents involves the receipt of data from sources over the network with-
out installing additional software for monitoring. Non-Agent data collection methods include:
̶ Read data directly from security log files or databases;
̶ Receiving information from sources using standard protocols for transmitting information about security
events;
̶ Data collection by connecting to the program interface or the web service of the data source.
By the usage of agent-free data collection method, data collection can be carried out about security incidents, the
operability of the software, and other information that the source can provide.
The collection of data on security incidents using questionnaires (forms) is carried out by filling in special electronic
(paper) forms and then transferring them to information security monitoring personnel.
Data collection method using software includes information management systems on information security
threats, security control systems, inventory means of software and technical means, software and information protec-
tion tools, and so on [10].
Categories of ISM systems
All currently established and used ISM Systems can fall into one of the following categories.
SIEM (Security Information and Event Management) is a system that allows analyzing data obtained from
various sources in real-time. SIEM is a combination of Information Security Management and security event manage-
ment systems into a single security management system. The results of the analysis carried out by SIEM are presented
in a single interface, accessible to security analysts. This also facilitates the study of the corresponding characteristic
features of security events and allows analyzing the events that occur in order to respond to security threats in real-
time (Fig. 3). Sources of information for SIEM systems can be antivirus programs, authorization and authentication
systems, network screens, security walls, logs of network equipment, servers and workstations, intrusion detection and
prevention systems (IDS / IPS), information leakage prevention systems (DLP) and other programs [11].
Інформаційні системи
̶ questionnaires (forms);
̶ software.
Fig. 2. Methods for collecting information from different sources
A security monitoring agent is software installed on information infrastructure components and information
system nodes to gather the necessary information directly from a source. Monitoring agents can be used to collect
information on security incidents, software effectiveness, user behavior, and other information.
The method of collecting data without agents involves the receipt of data from sources over the network without
installing additional software for monitoring. Non-Agent data collection methods include:
̶ Read data directly from security log files or databases;
̶ Receiving information from sources using standard protocols for transmitting information about security
events;
̶ Data collection by connecting to the program interface or the web service of the data source.
By the usage of agent-free data collection method, data collection can be carried out about security incidents, the
operability of the software, and other information that the source can provide.
The collection of data on security incidents using questionnaires (forms) is carried out by filling in special
electronic (paper) forms and then transferring them to information security monitoring personnel.
Data collection method using software includes information management systems on information security
threats, security control systems, inventory means of software and technical means, software and information protection
tools, and so on [10].
Categories of ISM systems
All currently established and used ISM Systems can fall into one of the following categories.
SIEM (Security Information and Event Management) is a system that allows analyzing data obtained from
various sources in real-time. SIEM is a combination of Information Security Management and security event
management systems into a single security management system. The results of the analysis carried out by SIEM are
presented in a single interface, accessible to security analysts. This also facilitates the study of the corresponding
characteristic features of security events and allows analyzing the events that occur in order to respond to security
threats in real-time (Fig. 3). Sources of information for SIEM systems can be antivirus programs, authorization and
authentication systems, network screens, security walls, logs of network equipment, servers and workstations, intrusion
detection and prevention systems (IDS / IPS), information leakage prevention systems (DLP) and other programs [11].
Agent based Without agent Questionnaires
(forms) Software
Log Analysis
Log Collection
Event Correlation
Log Forensics
IT Compliance
App Log Monitoring
Object Access Auditing
Real-Time
User Activity Monitoring
Dashboards
Reporting
File Integrity Monitoring
Sistem & Device Log
Monitoring
Log Retention
SIEM
Fig. 3. Security Information and Event Management
406
Захист інформації
UBA (User Behavioral Analytics) – systems that collect and analyze all behaviors, including managed data,
used to manage fraudulent activities at the expense of financial threats with internal threats [12].
UEBA (User and Entity Behavioral Analytics) – systems aimed at searching for and detecting anomalies
in the behavior of users and various systems. A class of behavioral analysis systems has been established because
companies use many different data collection systems to ensure information security. At the same time, employees
are not always able to review all the information received and respond to potential events in a timely manner. UEBA
systems increase efficiency by compiling profiles and ensuring timely response to possible data leaks [13].
Employee monitoring and time recording systems are systems that allow the organization to analyze the
activities of employees and monitor the use of working time in the workplace, as well as control business processes,
solve several tasks related to confidential information leaks, and further investigate of incidents [14].
Different types of attack detection and detection systems are aimed at improving the overall protection of
the corporate network [14].
The architecture of the decision support system in information security monitoring systems
To ensure the efficiency of decision-making is necessary in order to quickly respond to security breaches
and incidents in information security monitoring systems. In order to support decision-makers and improve ana-
lytical activities in this area, the development of a system that supports decision-making in information security
monitoring systems is proposed.
A decision support system is a computer system that allows decision-makers to make more reasonable
and correct decisions based on analytical recommendations provided to them. The decision support system can be
created on the basis of various technologies, including OLAP (Online Analytical Processing) and Data Warehouse
(DW) (Fig. 4.) [15]. The OLAP concept was described in 1993 by Edgar Codd, a well-known database researcher
and author of the relational data model. OLAP is a key component of the database. This is a technology that collects,
stores, and analyzes multidimensional data. Performs multidimensional, operational, and analytical data processing
in real-time. For the preparation of reports, the construction of forecast scenarios, and statistical calculations based
on large information systems with a complex structure are intended [16]. Through OLAP technology, the original
data is converted into information that can be used for decision-making. We can visualize the results of the analysis
and present the data in the form of graphs.
A warehouse is a place where all analytical information is collected for decision-making. ETL (Extract,
Transform, Load) is a three-step process called extraction, conversion, and loading that collects data from multiple
sources in a single parent repository.
̶ Extraction - extraction of data from external sources in an understandable format;
̶ Transformation - the conversion of primary data into suitable structures for the establishment of an
analytical system;
̶ Loading - uploading data to the warehouse.ETL processing is usually done by software, but can also be
done manually by system operators. Unnecessary data is cleaned up on the basis of statistical or expert
methods [17].
Figure 4 presents the architectural-technological model of the system that supports decision-making
for IMS.
At the first level, data sources are identified for ISM. The source of the data can be CERTs created within
an organization, a region, a country, network antiviruses, OS logs, security scanners, network equipment, and so on.
At the second level, the process of collecting primary data from various sources should be carried out for
the ISM system. Data can be collected from sources within an organization, a region, or a country. Data collection
can be done with agent programs, without agents, questionnaires (paper or electronic), or software. To ensure the
high quality of the data before it falls into a single Database, this may be necessary to clean it and delete unneces-
sary data. Therefore, in the intermediate stage, during the transition to the third level, the data enters the field of data
purification, and the ETL process is carried out as an intermediate stage.
Depending on the issue set at the third level, data on security incidents collected from sources within an
organization, region, or country by means of data collection methods (one or some of them may be) is collected in
the form of a separate database (DB) in one DW. Based on the data collected in each DB, reports are prepared for
analysis using OLAP technology.
On the fourth level, reports prepared for analysis on the basis of a separate database are collected in DW.
OLAP technology prepares reports for analysis by decision-makers on surveys sent to the data warehouse. Analysis
of security incidents collected from different sources within one organization, one region, or one country allow to
determine and assess the state of information security within an organization, one region, or one country, and to
identify the sources of threats.
Conclusion and Future Scope
The rapid development of the global Internet and ICT, and the impact on all areas of human activity,
raises the information security problem in CNs. The article analyzes ISM systems rapidly to detect cyber threats
and respond quickly to possible incidents for CNs to operate smoothly and reliably. Sources of primary data for
ISM systems were investigated, and categories of ISM systems were analyzed. As a result of the analysis, to en-
407
Захист інформації
sure the speed of decision-making for rapid response to security breaches and incidents was determined. In order
to support decision-makers and improve analytical activities in this area, a system has been developed to support
OLAP and data warehouse decision-making in ISM systems.
Інформаційні системи
investigated, and categories of ISM systems were analyzed. As a result of the analysis, to ensure the speed of decision-
making for rapid response to security breaches and incidents was determined. In order to support decision-makers and
improve analytical activities in this area, a system has been developed to support OLAP and data warehouse decision-
making in ISM systems.
/
Fig. 4. Architectural-technological model of Decision Support System for ISM systems
References
1. GRAHAM D. (2010). Cyber threats and the law of war. J. Nat'l Sec. L. & Pol'y Т. 4. P. 87.
2. АLGULIEV R. et al. (2014). Analysis of methods for network security monitoring. Problems of Information Technology. P. 60-68.
3. MUZALEVSKIY F. Information security monitoring. (in Russian). Available from: https://rtmtech.ru/articles/monitoring-informatsionnoj-
bezopasnosti. [Accessed 14/04/2022].
4. LITTLEWORT G. et al. (2011). The computer expression recognition toolbox (CERT). IEEE International Conference on Automatic Face
& Gesture Recognition (FG). IEEE. P. 298-305.
5. Software Engineering Institute. Available from: https://www.sei.cmu.edu/about/divisions/cert/index.cfm [Accessed 04/03/2020].
6. YAZOV YU. K. & SOLOVYOV S. V. (2015). Protection of information in information systems from unauthorized access. Kvarta. P. 357-
440. (in Russian)
Data Warehouse
Data sources
СERT Antivirus
systems OS logs
Security
scanners
Network
equipment ...
Data collection methods
Data processing and storage
Agent based Without agent Questionnaires
(forms) Software
DB1 Data Warehouse
...
Inquiry, report, analysis
OLAP
Visualization of
analysis results
DB2 DBn
Inquiry, report, analysis
OLAP
Inquiry, report, analysis
OLAP
Inquiry, report, analysis
OLAP
ETL, Data Cleaning
Fig. 4. Architectural-technological model of Decision Support System for ISM systems
References
1. GRAHAM D. (2010). Cyber threats and the law of war. J. Nat’l Sec. L. & Pol’y Т. 4. P. 87.
2. АLGULIEV R. et al. (2014). Analysis of methods for network security monitoring. Problems of Information Technology. P. 60-68.
3. MUZALEVSKIY F. Information security monitoring. (in Russian). Available from: https://rtmtech.ru/articles/monitoring-informatsionnoj-
bezopasnosti. [Accessed 14/04/2022].
4. LITTLEWORT G. et al. (2011). The computer expression recognition toolbox (CERT). IEEE International Conference on Automatic Face
& Gesture Recognition (FG). IEEE. P. 298-305.
5. Software Engineering Institute. Available from: https://www.sei.cmu.edu/about/divisions/cert/index.cfm [Accessed 04/03/2020].
6. YAZOV YU. K. & SOLOVYOV S. V. (2015). Protection of information in information systems from unauthorized access. Kvarta. P.
357-440. (in Russian)
7. BARRINGER H. et al. (2010). Formal analysis of log files. Journal of aerospace computing, information, and communication. Т. 7. No. 11. P.
365-390.
8. HOLM H. (2012). Performance of automated network vulnerability scanning at remediating security issues. Computers & Security. Т. 3.
No. 2. P. 164-175.
9. CôRTES H. & SANTOS P. & DA SILVA. & FILHO J. I. (2022). Monitoring electrical systems data-network equipment by means of
Fuzzy and Paraconsistent Annotated Logic. Expert Systems with Applications. P. 115865.
10. LETHBRIDGE T. C. & SIM S. E. & Singer J. (2005). Studying software engineers: Data collection techniques for software field
studies. Empirical software engineering. Т. 10. No. 3. P. 311-341.
11. KARLZEN H. (2009). An Analysis of Security Information and Event Management Systems: The Use of SIEMs for Log Collection. Manage-
ment. and Analysis. P. 45
12. BERNASCHINA C. et al. A big data analysis framework for model-based web user behavior analytics. International Conference on Web En-
gineering. Springer. Cham. P. 98-114.
13. SHASHANKA M. & SHEN M. Y. & WANG J. (2016). User and entity behavior analytics for enterprise security. IEEE International
Conference on Big Data (Big Data). IEEE. P. 1867-1874.
408
Захист інформації
14. KUFEL L. (2012). Security event monitoring in a distributed systems environment. IEEE security & privacy. Т. 11. No. 1. P. 36-43.
15. CODD E. F. & CODD S. B. & SALLEY C. T. (1993). Providing Olap. On-line Analytical Processing to User-Analists: An IT Man-
date. Associates. Т. 19.
16. KRZYSZTOF. J. CIOS. (2007). Data Mining: A Knowledge Discovery Approach. Springer. P. 123.
17. NABIBAYOVA G. (2011). About an application of OLAP-technology in decision making support systems. 5th International Conference on
Application of Information and Communication Technologies (AICT). IEEE. P. 1-4.
Received 17.07.2022
About the authors:
Dashdamirova Konul Qadim
PhD student and senior researcher
Institute of Information Technologies
Azerbaijan National Academy of Science
senior research associate.
Publications in foreign journals – 4
http://orcid.org/0000-0003-0365-6139
Place of work:
Institute of Information Technologies
Azerbaijan National Academy of Science
Azerbaijan Republic, Baku, B.Vahabzade str., 9A
Phone: (994 12) 539 01 67
E-mail: konulahmed@gmail.com
Прізвища та ініціали авторів і назва доповіді англійською мовою:
K.Q. Dashdamirova
Development of decision support system using
OLAP-technologies for information security
monitoring systems
Прізвища та ініціали авторів і назва доповіді українською мовою:
K.К. Дашдамірова
Розвиток системи підтримки рішень з використанням
OLAP-технологій для системи моніторингу інформаційної безпеки
|
| id | pp_isofts_kiev_ua-article-541 |
| institution | Problems in programming |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T09:41:21Z |
| publishDate | 2023 |
| publisher | PROBLEMS IN PROGRAMMING |
| record_format | ojs |
| resource_txt_mv | ppisoftskievua/4c/4394bbb5a542adc6ad718fbe4d0f1a4c.pdf |
| spelling | pp_isofts_kiev_ua-article-5412023-06-25T08:02:24Z Development of decision support system using OLAP-technologies for information security monitoring systems Розвиток системи підтримки рішень з використанням OLAP-технологій для системи моніторингу інформаційної безпеки Dashdamirova, K.Q. Information Security; Information Security Monitoring; SIEM; UBA; OLAP; Data warehouse UDC 681.3 інформаційна безпека; моніторинг інформаційної безпеки; SIEM; UBA; OLAP, сховище даних УДК 681.3 The article highlighted the need for continuous monitoring of the computer networks (CN) for information security and analyzed the sources of data for information security monitoring (ISM). Methods of data collection from various sources have been investigated, and categories of ISM systems have been studied. The architectural-technological model of the system supporting decision-making based on OLAP (Online Analytical Processing) and data warehouse has been proposed for quick response to security-related incidents and detected incidents in ISM systems.Prombles in programming 2022; 3-4: 403-408 У статті висвітлено необхідність постійного моніторингу комп’ютерних мереж з метою забезпечення інформаційної безпеки та проаналізовано джерела даних для моніторингу інформаційної безпеки. Досліджено методи збору даних з різних джерел, досліджено категорії систем моніторингу інформаційної безпеки. Запропоновано архітектурно-технологічну модель системи підтримки прийняття рішень на основі OLAP (Online Analytical Processing) і сховища даних для швидкого реагування на інциденти безпеки та виявлені інциденти в системах моніторингу інформаційної безпеки.Prombles in programming 2022; 3-4: 403-408 PROBLEMS IN PROGRAMMING ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ ПРОБЛЕМИ ПРОГРАМУВАННЯ 2023-01-23 Article Article application/pdf https://pp.isofts.kiev.ua/index.php/ojs1/article/view/541 10.15407/pp2022.03-04.403 PROBLEMS IN PROGRAMMING; No 3-4 (2022); 403-408 ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ; No 3-4 (2022); 403-408 ПРОБЛЕМИ ПРОГРАМУВАННЯ; No 3-4 (2022); 403-408 1727-4907 10.15407/pp2022.03-04 en https://pp.isofts.kiev.ua/index.php/ojs1/article/view/541/594 Copyright (c) 2023 PROBLEMS IN PROGRAMMING |
| spellingShingle | Information Security Information Security Monitoring SIEM UBA OLAP Data warehouse UDC 681.3 Dashdamirova, K.Q. Development of decision support system using OLAP-technologies for information security monitoring systems |
| title | Development of decision support system using OLAP-technologies for information security monitoring systems |
| title_alt | Розвиток системи підтримки рішень з використанням OLAP-технологій для системи моніторингу інформаційної безпеки |
| title_full | Development of decision support system using OLAP-technologies for information security monitoring systems |
| title_fullStr | Development of decision support system using OLAP-technologies for information security monitoring systems |
| title_full_unstemmed | Development of decision support system using OLAP-technologies for information security monitoring systems |
| title_short | Development of decision support system using OLAP-technologies for information security monitoring systems |
| title_sort | development of decision support system using olap-technologies for information security monitoring systems |
| topic | Information Security Information Security Monitoring SIEM UBA OLAP Data warehouse UDC 681.3 |
| topic_facet | Information Security Information Security Monitoring SIEM UBA OLAP Data warehouse UDC 681.3 інформаційна безпека; моніторинг інформаційної безпеки; SIEM; UBA; OLAP сховище даних УДК 681.3 |
| url | https://pp.isofts.kiev.ua/index.php/ojs1/article/view/541 |
| work_keys_str_mv | AT dashdamirovakq developmentofdecisionsupportsystemusingolaptechnologiesforinformationsecuritymonitoringsystems AT dashdamirovakq rozvitoksistemipídtrimkiríšenʹzvikoristannâmolaptehnologíjdlâsistemimonítoringuínformacíjnoíbezpeki |