Analysis of modern tools, methods of audit and monitoring of database security
Article Sidebar
Open full text
Issue Vol. 15 No. 4 (2025)
-
Control of the magnetic levitation using a PID controller with adaptation based on linear interpolation logic and genetic algorithm
Dominik Fila, Andrzej Neumann, Bartosz Olesik, Jakub Pawelec, Kamil Przybylak, Mateusz Ungier, Dawid Wajnert5-9
-
Development of a system for predicting failures of bagging machines
Nataliia Huliieva, Nataliia Lishchyna, Viktoriya Pasternak, Zemfira Huliieva10-13
-
Development and verification of a modular object-oriented fuzzy logic controller architecture for customizable and embedded applications
Rahim Mammadzada14-24
-
Mechanical fracture energy and structural-mechanical properties of meat snacks with beekeeping additives
Artem Antoniv, Igor Palamarchuk, Leonora Adamchuk, Marija Zheplinska25-31
-
Modelling of dynamic processes in a nonholonomic system in the form of Gibbs-Appell equations on the example of a ball mill
Volodymyr Shatokhin, Yaroslav Ivanchuk, Vitaly Liman, Sergii Komar, Oleksii Kozlovskyi32-38
-
Real-time Covid-19 diagnosis on embedded IoT platforms
Elmehdi Benmalek, Wajih Rhalem, Atman Jbari, Abdelilah Jilbab, Jamal Elmhamdi39-45
-
Hybrid models for handwriting-based diagnosis of Parkinson's disease
Asma Ouabd, Achraf Benba, Abdelilah Jilbab, Ahmed Hammouch46-50
-
Computer system for diagnostic and treatment of unilateral neglect syndrome
Krzysztof Strzecha, Agata Bukalska-Strzecha, Krzysztof Kurzdym, Dominik Sankowski51-55
-
Informatics and measurement in healthcare: deep learning for diabetic patient readmission prediction
Shiva Saffari, Mahdi Bahaghighat56-64
-
Optimization of non-invasive glucose monitoring accuracy using an optical sensor
Nurzhigit Smailov, Aliya Zilgarayeva, Sergii Pavlov, Balzhan Turusbekova, Akezhan Sabibolda65-70
-
Stochastic multi-objective minimax optimization of combined electromagnetic shield based on three-dimensional modeling of overhead power lines magnetic field
Borys Kuznetsov, Tatyana Nikitina, Alexander Kutsenko, Ihor Bovdui, Kostiantyn Czunikhin, Olena Voloshko, Roman Voliansky, Viktoriia Ivannikova71-75
-
Advanced energy management strategies for AC/DC microgrids
Zouhir Boumous, Samira Boumous, Tawfik Thelaidjia76-82
-
Experimental study of a multi-stage converter circuit
Kyrmyzy Taissariyeva, Kuanysh Muslimov, Yerlan Tashtay, Gulim Jobalayeva, Lyazzat Ilipbayeva, Ingkar Issakozhayeva, Akezhan Sabibolda83-86
-
Deep learning-based prediction of structural parameters in FDTD-simulated plasmonic nanostructures
Shahed Jahidul Haque, Arman Mohammad Nakib87-94
-
Development of an algorithm for calculating ion exchange processes using the Python ecosystem
Iryna Chub, Oleksii Proskurnia, Kateryna Demchenko, Oleksandr Miroshnyk, Taras Shchur, Serhii Halko95-99
-
Intelligent model for reliability control and safety in urban transport systems
Anastasiia Kashkanova, Alexander Rotshtein, Andrii Kashkanov, Denis Katelnikov100-107
-
Analysis of the interaction of components of a modular parcel storage system using UML diagrams
Lyudmila Samchuk, Yuliia Povstiana, Anastasia Hryshchuk108-116
-
Evaluating modified pairing insertion heuristics for efficient dial-a-ride problem solutions in healthcare logistics
Rodolfo Eleazar Pérez Loaiza, Aaron Guerrero-Campanur, Edmundo Bonilla Huerta117-123
-
Analysis of modern tools, methods of audit and monitoring of database security
Kateryna Mykhailyshyn, Oleh Harasymchuk, Oleh Deineka, Yurii Dreis, Volodymyr Shulha, Yuriy Pepa124-129
-
Improving underwater visuals by fusion of Deep-Retinex and GAN for enhanced image quality in subaquatic environments
Anuradha Chinta, Bharath Kumar Surla, Chaitanya Kodali130-136
-
The mathematical method for assessing the cybersecurity state of cloud services
Yevheniia Ivanchenko, Volodymyr Shulha, Ihor Ivanchenko, Yevhenii Pedchenko, Mari Petrovska137-141
-
Evaluation of the performance of LLMs deployments in selected cloud-based container services
Mateusz Stęgierski, Piotr Szpak, Sławomir Przyłucki142-150
-
Implementing traits in C# using Roslyn Source Generators
Mykhailo Pozur, Viktoria Voitko, Svitlana Bevz, Serhii Burbelo, Olena Kosaruk151-157
-
Impact of customizable orchestrator scheduling on machine learning efficiency in edge environments
Konrad Cłapa, Krzysztof Grudzień, Artur Sierszeń158-163
-
Reconfigured CoARX architecture for implementing ARX hashing in microcontrollers of IoT systems with limited resources
Serhii Zabolotnii, Inna Rozlomii, Andrii Yarmilko, Serhii Naumenko164-169
-
Integral assessment of the spring water quality with the use of fuzzy logic toolkit
Vyacheslav Repeta, Oleksandra Krykhovets, Yurii Kukura170-176
-
Selected issues concerning fibre-optic bending sensors
Les Hotra, Jacek Klimek, Ihor Helzhynskyy, Oksana Boyko, Svitlana Kovtun177-181
Archives
-
Vol. 15 No. 4
2025-12-20 27
-
Vol. 15 No. 3
2025-09-30 24
-
Vol. 15 No. 2
2025-06-27 24
-
Vol. 15 No. 1
2025-03-31 26
-
Vol. 14 No. 4
2024-12-21 25
-
Vol. 14 No. 3
2024-09-30 24
-
Vol. 14 No. 2
2024-06-30 24
-
Vol. 14 No. 1
2024-03-31 23
-
Vol. 13 No. 4
2023-12-20 24
-
Vol. 13 No. 3
2023-09-30 25
-
Vol. 13 No. 2
2023-06-30 14
-
Vol. 13 No. 1
2023-03-31 12
-
Vol. 12 No. 4
2022-12-30 16
-
Vol. 12 No. 3
2022-09-30 15
-
Vol. 12 No. 2
2022-06-30 16
-
Vol. 12 No. 1
2022-03-31 9
-
Vol. 11 No. 4
2021-12-20 15
-
Vol. 11 No. 3
2021-09-30 10
-
Vol. 11 No. 2
2021-06-30 11
-
Vol. 11 No. 1
2021-03-31 14
Main Article Content
DOI
Authors
kateryna.mykhailyshyn.kb.2022@lpnu.ua
Abstract
The mismatch between modern technological innovations and traditional approaches to information security can significantly affect the effectiveness of database monitoring systems. This paper examines the ethical and legal aspects of database monitoring, taking into account current regulatory requirements and the importance of maintaining data confidentiality. The study also evaluates the use of each tool to determine their effectiveness in real-world conditions, the possibility of improving the functional characteristics of monitoring systems, their adaptation to new technologies and increasing the overall level of information protection.
Keywords:
References
[1] Cinar O. et al.: Database Security in Private Database Clouds. International Conference on Information Science and Security (ICISS), Pattaya, Thailand, 2016, 1–5 [http://doi.org/10.1109/ICISSEC.2016.7885847].
[2] Deineka O. et al.: Designing Data Classification and Secure Store Policy According to SOC 2 Type II. CEUR Workshop Proceedings, 2024, 3654, 398–409 [https://ceur-ws.org/Vol-3654/short7.pdf].
[3] Devara S. R., Azad C.: Improved Database Security Using Cryptography with Genetic Operators. SN Computer Science 4(5), 2023, 570 [http://doi.org/10.1007/s42979-023-01990-z].
[4] Dou K. et al.: Research on Mainstream Data Base Security Analysis Technology of Big Data Platform. IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C). Hainan, China, 2021, 994–998 [http://doi.org/10.1109/QRS-C55045.2021.00150].
[5] Dreis Yu. et al.: Model to Formation Data Base of Internal Parameters for Assessing the Status of the State Secret Protection. Cybersecurity Providing in Information and Telecommunication Systems 3654, 2024, 277–289 [https://ceur-ws.org/Vol-3654/paper23.pdf].
[6] Falchenko S. et al.: Method of Fuzzy Classification of Information with Limited Access. IEEE 2nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020). Kyiv, Ukraine, 2020, 255–259 [http://doi.org/10.1109/ATIT50783.2020.9349358].
[7] Flores D. A. et al.: Implementing Chain of Custody Requirements in Database Audit Records for Forensic Purposes. IEEE Trustcom/BigDataSE/ICESS, 2017, 675–682 [http://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.299].
[8] Hong S. et al.: Data Auditing for Intelligent Network Security Monitoring. IEEE Communications Magazine 61(3), 2023, 74–79 [http://doi.org/10.1109/MCOM.003.2200046].
[9] Huang Q. et al.: A Logging Scheme for Database Audit. Second International Workshop on Computer Science and Engineering. Qingdao, China, 2009, 390–393 [http://doi.org/10.1109/WCSE.2009.837].
[10] Huijie W.: A Security Framework for Database Auditing System. 10th International Symposium on Computational Intelligence and Design. Hangzhou, China, 2017, 350–353 [http://doi.org/10.1109/ISCID.2017.64].
[11] Ivanichenko Y. et al.: Restricted Information Identification Model. Cybersecurity Providing in Information and Telecommunication Systems 3288, 2022, 89–95 [https://ceur-ws.org/Vol-3288/short5.pdf].
[12] Kehe Wu et al.: The Design and Implementation of Database Audit System Framework. IEEE 5th International Conference on Software Engineering and Service Science, 2014 [http://doi.org/10.1109/ICSESS.2014.6933628].
[13] Korchenko O. et al.: Tuple Model for Forming a Database of Primary Parameters for Assessing the State Secret Protection Status. Ukrainian Scientific Journal Infjrmation Security 28(1), 2022, 35–42 [http://doi.org/10.18372/2225-5036.28.16911].
[14] Lakhdhar Y. et al.: Active, Reactive and Proactive Visibility-Based Cyber Defense for Defending Against Attacks on Critical Systems. International Wireless Communications and Mobile Computing (IWCMC). Limassol, Cyprus, 2020, 439–444 [http://doi.org/10.1109/IWCMC48107.2020.9148400].
[15] Liegang Han et al.: HDTSM: Hybrid Dynamic Token-based Security Mechanism for Database Protection in E-Government Service Systems. International Conference on Artificial Intelligence and Automation Control (AIAC), 2023, 94–98 [http://doi.org/10.1109/AIAC61660.2023.00029].
[16] Martseniuk Y. et al.: Automated Conformity Verification Concept for Cloud Security. CEUR Workshop Proceedings 3654, 2024, 25–37 [https://ceur-ws.org/Vol-3654/paper3.pdf].
[17] Martseniuk Y. et al.: Shadow IT risk analysis in public cloud infrastructure. Cyber Security and Data Protection 2024, 22–31 [https://ceur-ws.org/Vol-3800/paper3.pdf].
[18] Martseniuk Y. et al.: Universal Centralized Secret Data Management for Automated Public Cloud Provisioning. Cybersecurity Providing in Information and Telecommunication Systems 2, 2024, 72–81 [https://ceur-ws.org/Vol-3826/paper7.pdf].
[19] Motwani R. et al.: Auditing SQL Queries. IEEE 24th International Conference on Data Engineering. Cancun, Mexico, 2008, 287–296 [http://doi.org/10.1109/ICDE.2008.4497437].
[20] Mousa A. et al.: Database Security Threats and Challenges. 8th International Symposium on Digital Forensics and Security (ISDFS). Beirut, Lebanon, 2020, 1–5 [http://doi.org/10.1109/ISDFS49300.2020.9116436].
[21] Ozkan-Okay M. et al.: A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions. IEEE Access 12, 2024, 12229–12256 [http://doi.org/10.1109/ACCESS.2024.3355547].
[22] Paradisi M.: Proactive and Predictive Risk Management in Aviation Safety: A Corporate Strategic Approach. IEEE International Workshop on Technologies for Defense and Security (TechDefense). 2023, 34–39 [http://doi.org/10.1109/TechDefense59795.2023.10380870].
[23] Semančik L.: Recording of Data Monitoring Access to Databases Using Triggers. Communication and Information Technologies (KIT). Vysoke Tatry, Slovakia, 2019, 1–5 [http://doi.org/10.23919/KIT.2019.8883478].
[24] Seok-Woo Lee et al.: Database Security System Based on User Identification. Journal of Digital Contents Society 25(4), 2024, 1079–1085 [http://doi.org/10.9728/dcs.2024.25.4.1079].
[25] Shevchenko S. et al.: Protection of Information in Telecommunication Medical Systems Based on a Risk-Oriented Approach, Cybersecurity Providing in Information and Telecommunication Systems 3421, 2023, 158–167 [https://ceur-ws.org/Vol-3421/paper16.pdf].
[26] Shevchuk D. et al.: Designing Secured Services for Authentication, Authorization and Accounting of Users (short paper). CPITS II, 2023, 217–225 [https://ceur-ws.org/Vol-3550/short4.pdf].
[27] Skladannyi P. et al.: Model to Formation Data Base of Secondary Parameters for Assessing Status of the State Secret Protection. Conference Cyber Security and Data Protection, Lviv, Ukraine, 3800, 2024, 1–11 [https://ceur-ws.org/Vol-3800/paper1.pdf].
[28] Wang Y. et al.: The Overview of Database Security Threats’ Solutions: Traditional and Machine Learning. Journal of Information Security 12, 2021, 34–55 [http://doi.org/10.4236/jis.2021.121002].
[29] Yongzheng Wu et al.: A User-Level Framework for Auditing and Monitoring. 21st Annual Computer Security Applications Conference (ACSAC'05). Tucson, USA, 2005, 101–105 [http://doi.org/10.1109/CSAC.2005.8].
[30] GDE DSM Installation Guide v3.0.0.2. [https://www.ibm.com/support/ pages/system/files/inline-files/$FILE/GDE_DSM_Install_Guide_v3.0.0.2_ v1_0.pdf].
[31] IBM Security Guardium Data Protection – Incident management. [https://icore.kz/upravlenie-inczidentami/ibm-security-guardium-data-protection].
[32] Integrity Oracle Security Blog – What is Oracle Audit Vault. [https://www.integrigy.com/oracle-security-blog/what-oracle-audit-vault].
[33] Microsoft Learn – SQL Server Audit (Database Engine). [https://learn.microsoft.com/en-us/sql/relational-databases/security/auditing/ sql-server-audit-database-engine?view=sql-server-ver16].
[34] Oracle Documentation Audit Vault and Database Firewall. [https://docs.oracle.com/en/database/oracle/audit-vault-database-firewall/20/sigli/index.html#GUID-E11B3C13-8BD4-449F-8E9E-27B9898D778D].
[35] SecureSphere Management Solutions. [https://www.imperva.com/resources/datasheets/DS_SecureSphere_Management_Solutions.pdf].
[36] Splunk – The Essential Guide to Data. [https://www.splunk.com/en_us/pdfs/ebooks/the-essential-guide-to-data.pdf].
[37] What Is Splunk & What Does It Do? A Splunk Intro. [https://www.splunk.com/en_us/blog/learn/what-splunk-does.html].
Article Details
Abstract views: 0

