Modern Information Security

Title

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Content

2025-06-28T17:46:34+00:00

Content

MODELING OF PROCESSES IN AN OPEN-CLOSED AUTOMATIC CONTROL SYSTEM WITH HYDRAULIC DRIVE

2025-06-28T17:46:12+00:00

The article investigates the properties of an open-type automatic control system as a component of a unified stabilization
system for a firearm on a highly mobile transport base. A hydraulic drive is proposed as an actuator in the stabilization system.
According to the results of the preliminary analysis, this type of actuator satisfies the conditions for the stabilization system to
function. To study the dynamics of processes in an open-type automatic control system (ACS), the transfer function of the
system is derived in the work. The stages of mathematical modeling of the components of an open-type automatic control system
are presented: a control signal source, an electromagnetic valve for controlling the spool mechanism, and a hydraulic cylinder.
The control signal source is presented as a linear dynamic link. The dynamics of the electromagnetic valve is modeled by a firstorder equation that takes into account the inertia of converting an electrical signal into a working fluid flow rate. The hydraulic
cylinder is presented as an integrating link that establishes a connection between the fluid flow rate and the piston movement
(load). Based on the transfer functions of the components, the overall transfer function of the system is determined, taking into
account inertial characteristics (mass of moving parts), damping factors and hydraulic dynamics. The transient and frequency
characteristics of the open-loop automatic control system are simulated, which confirms the adequacy of the model. The
proposed approach can be used not only for analyzing the stability and quality of control of hydraulic drives in industrial and
transport vehicles, but also as recommendations for building hydraulic drives under the guidance of mathematical models or
artificial intelligence.
Keywords: automatic control system, transfer function, hydraulic cylinder, solenoid valve, transient, frequency
characteristics, mathematical model.

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з заданої точності позиціювання робочого органа, швидкодії і характеру перехідного процесу. Вісник
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10.33216/1998-7927-2022-272-2-15-22.

IMPROVED METHOD FOR DETECTING FALSE INFORMATION BASED ON EXPERT ASSESSMENT

2025-06-28T17:46:21+00:00

The method of expert evaluation is an ancient scientific method that allows to obtain an objective assessment based
on a certain set of individual expert opinions. The word "expert" (expertus) in Latin means "experienced", which, in turn,
comes from the word "experire" - to explore. An expert is a person (specialist) entrusted with expressing an opinion on a
controversial or complex case, as humanity has always tried to take into account the opinion of highly qualified specialists
in various fields of life in difficult situations [2].
The article improves the method of detecting false information based on the method of expert evaluation. The
Delphi expert evaluation method was chosen as the basic method for improvement. This is because it has undoubted
advantages over methods based on conventional statistical processing of individual survey results. Unlike the existing
approach, the improved method allows for the selection of experts rather than adjusting the answers of experts to obtain
the required result.
The main feature is that the experts are selected by averaging the scores for each expert. Specifically, the selfassessment of the expert and the assessment of the same expert by the working group. This allows you to reduce the error
of the expert's real assessment.
The ability to set the confidence interval for the assessment of false information will allow obtaining results that
satisfy the task of detecting false information with proper accuracy. However, this leads to the task of optimizing the
evaluation criteria and the time for solving the task. Therefore, the direction of further research is the task of optimizing
the evaluation criteria.
The scientific novelty lies in substantiating and assessing the comparative importance of the factors limiting the
appointment of each individual expert to detect false information using the method of group expert assessment.
Keywords: false information, expert opinions, quartile, median, confidence interval, limitations.

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CYBERSECURITY PROBLEMS IN ORGANIZATIONS WITH REMOTE WORK

2025-06-28T17:46:35+00:00

The rapid spread of remote work in the world creates new challenges for ensuring effective and secure digital interaction
in organizations. The purpose of this study is a comprehensive analysis of modern approaches, tools and organizational and
legal means used to organize secure digital interaction in remote work. To achieve this goal, the method of analyzing literary
sources was used, which allowed to systematize information on technological solutions, management practices and regulatory
requirements related to remote work.
The main key aspects were analyzed: digital platforms and services for communication and collaboration, user device
management and the Bring Your Own Device (BYOD) concept, as well as legal regulation of the field of cybersecurity and
privacy. The study results found that the use of unified platforms for managing corporate services reduces the fragmentation of
the digital environment and the risks of data leakage; providing employees with secure corporate devices or implementing clear
BYOD policies minimizes the main cyber threats; Compliance with international standards and national legislation in the field
of information protection ensures the legal compliance of the activities of a distributed team. A comprehensive approach that combines modern technological tools, effective management and compliance with legal norms allows you to increase the level
of information security and the efficiency of remote work, minimizing potential risks.
Keywords: cybersecurity, cloud security, remote work, BYOD, legal regulation.

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ASSESSMENT OF THE STATE OF CYBERSECURITY OF CRITICAL INFRASTRUCTURE USING AI

2025-06-28T17:46:48+00:00

This study examines the use of artificial intelligence as a tool for assessing the state of cybersecurity of critical
infrastructure. This approach is relevant in view of the growing threat of the use of artificial intelligence technologies by
cybercriminals. Thanks to the power of artificial intelligence, it has become possible to analyze large data sets to identify patterns
and anomalies that indicate potential attacks, including previously unknown variants. This allows for proactive protection, which
includes timely warning of threats and data integrity checks, which contribute to their confident recovery after attacks.
Artificial intelligence also contributes to the localization of threats by analyzing the scale of cyberattacks, determining
the radius of their spread, which allows for effective isolation of affected systems and minimizing their impact on the
infrastructure. In addition, artificial intelligence algorithms optimize the recovery process, reducing system downtime, reducing
losses and ensuring high adaptability to new challenges in the cyber environment.
Given the significant capital intensity of the measures, the approach to integrating artificial intelligence requires careful
selection of the platform, concept and tools. The development and implementation of solutions in the field of cyber protection
is mostly provided by international companies, which affects the possibilities of using such technologies by owners and users
of critical infrastructure. Thus, the implementation of artificial intelligence to assess the state of cybersecurity of critical
infrastructure is not only a promising direction of cybersecurity, but also a prerequisite/requirement for creating a resilient
critical infrastructure that is able to effectively adapt to new cyber threats/cyber-attacks/cyber incidents.
In addition, recommendations are proposed for choosing an AI model/platform/tools for large companies - owners/users
of AI in various sectors of the economy, since the issue of choosing/using AI models/platforms/tools requires including in the
selection criteria such factors as the impact on the state of national security and geopolitical strategic relations between countries.
Keywords: vulnerabilities, state security, defense systems, cybersecurity, cyber defense, sustainability and resilience,
critical infrastructure, information security management, model and tools, analysis, security assessment, artificial intelligence.

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Report&sort=relevancy

ANALYSIS OF THE RESISTANCE OF STEGANOALGORITHMS TO GEOMETRIC ATTACKS AND COMPRESSION

2025-06-28T17:46:56+00:00

The analysis of the stability of steganographic methods of hiding in the spatial domain to attacks common in open and
closed channels, such as geometric transformations and compression, was carried out. The impact of these attacks on the stability
of the steganochannel operation was assessed and methods for increasing the stability to such attacks were proposed. Various
types of attacks based on affine transformations and their impact on the quality of information hiding were investigated.
Attention was focused on preserving the integrity of the message during such attacks.
The study evaluates the possibility of using different types of messages and the impact of coding with repetition on the
stability of the steganosystem. A method for assessing the stability of attacks based on the bit error method was developed and
simulated, which was modified for analysis at the byte level in order to apply the results to different types of containers and
support streaming data.
The importance of the absence of the influence of the order of pixel placement when embedding a message is noted,
which allows minimizing the impact of geometric transformations on the embedded message. The resistance of the color space
modification algorithm to attacks is higher than that of the LSB method by 14-98%. LSB has a 10% higher resistance only to a
minor scaling attack. However, this difference does not allow us to call it practically suitable for use.
The influence of image resolution on the amount of embedded information in each of the methods is analyzed. Promising
directions for further research are analyzed by introducing block coding and using effective error correction methods and using
alternative container properties for embedding.
Keywords: steganography, geometric attacks, affine transformations, color space.

References
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ANALYSIS OF AUTHENTICATION MODELS AND ALGORITHMS BASED ON BIOMETRIC DATA

2025-06-28T17:47:07+00:00

User authentication is one of the key aspects of information security, which provides access control to resources and
protection of confidential data. Traditional authentication methods, such as passwords and PIN codes, have a number of
shortcomings, in particular, vulnerability to attacks such as brute force, phishing, and interception. In this regard, there is
growing interest in biometric authentication methods that provide a higher level of security and ease of use. The article considers
modern models and algorithms of biometric authentication, their advantages and disadvantages. The features of the use of
unimodal and multimodal systems are analyzed. Special attention is paid to promising methods for increasing the accuracy of
authentication and the security of biometric data storage. An analysis of modern research in this area is presented. The main
algorithms used in biometric authentication systems are also considered, including image processing methods, neural networks,
machine learning, and cryptographic technologies. The possibilities of using multi-factor authentication, which combines
biometric parameters with other methods of identity verification, which significantly increases the level of security, are
analyzed. The prospects for the development of biometric authentication systems are considered, in particular, the introduction of new technologies, such as artificial intelligence, blockchain and quantum cryptography. An analysis of possible risks
associated with biometric authentication is carried out. It is concluded that the use of biometric methods allows to significantly
increase the efficiency of authentication, reduce the risks of data compromise and ensure convenience for users, however, their
implementation requires taking into account issues of confidentiality, reliability and legal regulation. An authentication system
based on artificial intelligence, blockchain, quantum cryptography is proposed and its effectiveness is analyzed.
Keywords: biometric authentication, unimodal systems, multimodal systems, artificial intelligence, cryptography,
steganography.

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INCREASING THE EFFICIENCY OF STEGANOGRAPHY THROUGH THE USE OF IMAGE ENHANCEMENT METHODS AND ARTIFICIAL INTELLIGENCE MODELS

2025-06-28T17:47:15+00:00

The article investigates the problem of increasing the efficiency of steganographic methods through the use of modern
approaches to image enhancement. Particular attention is paid to preprocessing methods, as well as the use of deep neural
networks, such as ESRGAN, U-Net, and SteganoGAN. The results of experiments using adaptive contrast enhancement and
smoothing are presented, which allows increasing the hidden capacity of the container and reducing the probability of detecting
hidden data. The paper investigates the influence of preprocessing methods on the results of steganographic message hiding. It
was experimentally established that preprocessing of images significantly affects the efficiency of LSB steganography. The best
stealth (high PSNR and SSIM) and resistance to JPEG compression was demonstrated by the approach with adaptive texture
segmentation. Conversion to YCbCr also allows increasing stability without losing bandwidth. At the same time, histogram
equalization worsens stability due to increased contrast. Thus, adaptive preprocessing methods are advisable to use to improve
the security and quality of information hiding. A comparison of artificial intelligence models for steganography tasks was
conducted. In the course of the work, artificial intelligence models used in steganography tasks were analyzed. It was found that
the effectiveness of a specific architecture (for example, U-Net or SteganoGAN) significantly depends on the tasks, the type of
input data, the requirements for channel bandwidth, and the available computing resources. It was concluded that the adaptive
use of deep learning and image preprocessing methods allows to increase both the stability of hidden messages and their
invisibility, which is critically important for modern digital steganography.
Keywords: steganography, image enhancement, ESRGAN, deep learning, information protection, neural networks.

References
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Letters, 2022.

INCREASING THE EFFICIENCY OF STEGANOGRAPHY THROUGH THE USE OF IMAGE ENHANCEMENT METHODS AND ARTIFICIAL INTELLIGENCE MODELS

2025-06-28T17:47:21+00:00

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KEY ASPECTS OF THE UPDATED ISO/IEC 27002:2022 STANDARD

2025-06-28T17:47:33+00:00

The article analyzes the main changes made to ISO/IEC 27002:2022, a standard that contains detailed guidelines for
implementing information security measures. In particular, a key update is considered, which concerns the reduction of the
number of security measures (controls) from 114 to 93 by combining and optimizing them. Attention is drawn to the new
classification structure, according to which controls are now divided into four categories: organizational, human, physical, and
technological. Another innovation is considered in detail - the introduction of attributes, the use of which allows you to more
effectively filter, group, and apply security measures in accordance with the specific needs of the organization. The article also
describes 11 new controls, namely: information security when using cloud services, ICT readiness for business continuity,
configuration management, physical security monitoring, information deletion, data masking, threat intelligence, data leakage
prevention, activity monitoring, web content filtering, and secure coding. The changes introduced in ISO/IEC 27002:2022 are aimed at increasing the adaptability of the standard to the dynamic development of information technologies and meeting the
growing needs of organizations in the field of cybersecurity. This standard can be used by security managers to select, implement
and document information protection measures in accordance with the requirements of ISO/IEC 27001:2022, which will
facilitate the audit and certification process.
Keywords: information security, information security management system, standard, ISO/IEC 27002:2013, ISO/IEC
27002:2022, security measures, controls.

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Outlook of Key Countries 2023-2028. URL: https://www.industryresearch.biz/ global-bring-your-own-device-byodindustry-23044218.
3. Right Scale State of the Cloud Report 2013. URL: https://www.slideshare.net/arms8586/ rightscale-state-ofthe-cloud-report-2013.
4. Flexera 2022 State of the Cloud Report. URL: https://m3comva1.frb.io/uploads/docs/ Flexera-State-of-theCloud-Report-2022.pdf.
5. ISO/IEC 27001:2022 Information security, cybersecurity and privacy protection — Information security
management systems — Requirements. URL: https://www.iso.org/standard/ 54534.html.
6. ISO/IEC 27002:2022 Information security, cybersecurity and privacy protection — Information security
controls. URL: https://www.iso.org/standard/75652.html.

A COMPREHENSIVE MODEL OF SECURITY INTEGRATION INTO THE DEVELOPMENT LIFE CYCLE FOR CLOUD ENVIRONMENTS

2025-06-28T17:47:39+00:00

This study proposes a comprehensive model specifically designed to address the security challenges associated with
modern cloud infrastructures. The proposed model ensures the implementation of security measures from initial planning to the
end of the application lifecycle, prioritizing continuous security implementation at all stages. The model focuses on integrating
security as an integral part of the development process. It involves ongoing risk management, regular audits, and driving
continuous innovation throughout the SDLC. Other key components of the extended model include security governance, safe
component decommissioning, monitoring, response, learning, and scaling.
The extended model encompasses 20 key components that form a complete set of actions required to securely develop,
deploy, and maintain modern software systems. It considers not only technical aspects, but also cultural and procedural factors,
which are the basis for sustainable security management.
Comparison with existing models demonstrates that the extended model not only addresses gaps in current practices, but
also offers a scalable solution that meets the dynamic nature of today's IT environments. The model's emphasis on continuous
innovation and adaptation helps organizations stay one step ahead of new threats and changing security requirements.
Keywords: software development lifecycle, SDLC, DevSecOps, cloud security, security management, continuous
integration.

References
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R. A. Khan та ін. IEEE Access. 2022. Т. 10. С. 5456–5481. URL: https://doi.org/10.1109/access.2022.3140181(дата
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open-source software over cloud (ADOC). Computers & Security. 2020. Т. 97. С. 101967.
URL: https://doi.org/10.1016/j.cose.2020.101967(дата звернення: 25.05.2025).
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ANALYSIS OF CYBER THREAT TRENDS AS AN IMPORTANT STAGE OF FINANCIAL SECTOR RISK MANAGEMENT

2025-06-28T17:47:46+00:00

Analysis of cyber threats to the financial sector updates the concept of a risk-based approach in the activities of financial
institutions and allows for timely response to incidents. Tracking and understanding cyber threat trends contribute to effective
cyber risk management. To determine the vector of changes in the threat landscape, it is important to take into account the
experience of different countries in order to adapt best practices to Ukrainian realities. In the conditions of a full-scale war,
Ukrainian financial institutions, in particular banks, demonstrated a noticeable increase in resilience to cyber-attacks. The
experience gained in such difficult conditions allowed banks to strengthen their technical and organizational capabilities to
counter incidents. An important role in this was played by the coordinated interaction of state bodies and private organizations,
CERT-UA, the activities of specialized units of Ukraine - the Cyber Police Department of the National Police of Ukraine, the
State Cyber Protection Center of the State Service for Special Communications and Information Protection of Ukraine, the
Critical Infrastructure Protection Department of the NBU, as well as interbank cooperation in the field of exchanging
information about threats, international cooperation in the field of ensuring cybersecurity in the banking sector. This approach
is the basis for increasing the speed of response to cyber incidents and will contribute to the overall strengthening of cyber
protection of the financial sector of Ukraine.
Keywords: cyber threat landscape of the financial sector, cyber resilience of banks, cybercriminal organizations, DDoS
attacks, CERT-UA, State Cyber Protection Center of the State Service for Special Communications and Information Protection
of Ukraine, NBU, MISP-UA.

References
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звернення: 23.03.2025.
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ANALYSIS OF METHODS FOR PROTECTING THE VOICE INFORMATION TRANSMISSION SYSTEM

2025-06-28T17:48:00+00:00

The article considers modern approaches to protecting voice information transmission systems in the face of growing
cyber threats, especially in the context of hybrid warfare and the actions of the legal regime of martial law. The emphasis is on
the importance of ensuring the confidentiality, integrity and availability of voice content transmitted via wired and wireless
communication channels in the civilian and military sectors. An analysis of classical and modern protection methods, including
cryptographic (AES, RSA, ECC), steganographic, adaptive and organizational and technical means, is carried out. The
feasibility of using SRTP, ZRTP protocols, as well as dynamic key management technologies, intrusion detection systems (IDS)
and acoustic and vibration shielding methods is substantiated. It is shown that the effectiveness of protection increases
significantly when combining several levels of security and adaptation to environmental conditions. The article presents a
comparative table of methods evaluation. The conclusions are supported by data from domestic and foreign scientific
publications, which allows identifying promising directions for the development of voice information protection systems.
Keywords: information protection; speech information; steganography; cryptography; adaptive methods;
communication systems; security of speech information transmission.

References
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METHODOLOGY FOR STUDYING THE SECURITY STATUS OF CLOUD TECHNOLOGIES USING OSINT TOOLS

2025-06-28T17:48:07+00:00

The article examines the current problem of ensuring cybersecurity of cloud storage in the context of rapid digital
transformation and the growing dependence of organizations on cloud technologies. The authors propose a systematic
methodology for assessing the security status of cloud environments using open-source intelligence (OSINT) tools, which allows
identifying potential vulnerabilities without direct interaction with the research object. The developed methodology covers the
full cycle of OSINT research: from goal setting and selection of relevant tools to data collection, analysis, and documentation.
Particular attention is paid to threats specific to cloud storage, such as misconfigurations, account compromise, unprotected
APIs, data leaks, and insider risks. Examples of OSINT tools and techniques for identifying these threats are presented (Shodan,
Censys, Google Dorks, Have I Been Pwned, etc.). The article also emphasizes the importance of an ethical approach to research,
emphasizing the need to comply with the law when collecting information from open sources. The advantages of OSINT as a
tool for safe, cost-effective and operational assessment of the level of security of cloud infrastructure are separately considered.
The proposed methodology is a valuable practical tool for cybersecurity professionals, auditors and researchers, allowing for
effective detection of vulnerabilities in
Keywords: cybersecurity, cloud storage, OSINT, open-source intelligence, data security, vulnerabilities, risk analysis.

References
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ANALYSIS OF OPPORTUNITIES TO IMPROVE THE SECURITY OF CLOUD INFRASTRUCTURE USING NLP AND ML

2025-06-28T17:48:14+00:00

As data volumes and the complexity of multi-cloud environments grow, ensuring cybersecurity of cloud infrastructure
is becoming an increasingly difficult task. Traditional approaches based on static rules, signature analysis and centralized SIEM
systems show limited effectiveness when working with dynamic resources and adaptive attacks, such as ART campaigns, insider
threats or zero-day exploits. This necessitates the implementation of intelligent analysis and response mechanisms that can
quickly correlate heterogeneous events and reduce the number of false positives. The integration of natural language processing
(NLP) and machine learning (ML) technologies opens up new opportunities for automating incident analytics, semantic parsing
of event logs (hereinafter referred to as logs) and classifying threats by risk level. NLP modules allow processing large arrays
of unstructured text data — event logs, user messages and configuration files — and identifying sociotechnical attack patterns.
ML algorithms, in turn, provide anomaly detection using classification, clustering, and behavioral analytics (UEBA), which
allows you to predict potential attacks before they are implemented. Modern cybersecurity concepts, in particular the Zero Trust
model and the Principle of Least Privilege (PoLP), combined with the Security as Code approach, create the basis for dynamic
access control and automated rights management. Architectural solutions combining Cloud IAM, PAM, and CIEM are
complemented by AI-driven mechanisms for real-time query context assessment and automated verification of excessive
privileges. This helps reduce response time and increase the adaptability of security policies. This study systematically reviewed
more than ten modern scientific publications covering practical implementations of intelligent DLP systems, automated threat
detection mechanisms in AWS, Azure, and GCP, as well as approaches to integrating NLP/ML into CI/CD processes and SOAR
platforms. Requirements for building adaptive, context-sensitive solutions are formulated, taking into account scalability,
interpretable artificial intelligence (Explainable AI) and compliance with ethical and legal norms (GDPR, ISO/IEC 27001). The
results of the study prove that a combined approach based on NLP and ML allows to significantly reduce the number of false
positives, reduce the average response time to incidents and increase the accuracy of detecting complex threats. The obtained
conclusions will be useful for IT departments, security engineers and DevOps teams seeking to optimize cyber protection
processes in dynamic multi-cloud environments.
Keywords: cybersecurity, cloud technologies, NLP, ML, Zero Trust, Security as Code, UEBA, DLP.

References
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RESEARCH ON THE EFFECTIVENESS OF XDR SOLUTIONS FOR DETECTING AND ELIMINATING THREATS

2025-06-28T17:48:29+00:00

In the context of digital transformation, when organizations’ dependence on IT infrastructure is rapidly increasing, the
level of cyber threats is also increasing. According to current data, the number of cyberattacks on organizations in 2024 increased
by 75% compared to the previous year, reaching 1876 incidents per week. In response to these challenges, the evolution of
protection tools is taking place - traditional solutions are being replaced by comprehensive XDR (Extended Detection and
Response) systems. The study focuses on a comparative analysis of XDR and EDR (Endpoint Detection and Response)
solutions, revealing their fundamental differences and practical effectiveness. XDR platforms provide advanced data collection
and analysis from various sources (network events, cloud services, email) instead of being limited to only end devices, which
allows you to form a holistic picture of the organization’s security. Special attention is paid to mechanisms for automating
memory forensics in XDR systems: it was investigated that modern platforms are capable of automating data collection from
RAM and deploying specialized DFIR utilities through the "remediation" mechanism. A practical comparison of the detection
of the same EDR and XDR threats was conducted using the example of a multi-phase phishing attack using LOLBINs, which
demonstrated the significant advantages of XDR in response speed and accuracy. It was established that XDR solutions
demonstrate higher efficiency due to the correlation of events from different sources, the use of machine learning and behavioral
analytics. The main XDR solutions on the market (CrowdStrike Falcon, SentinelOne Singularity, Microsoft Defender, Elastic
Security) and their features in the implementation of protection mechanisms were analyzed. The results of the study confirm
that the integration of XDR with additional systems (network devices, cloud services, authentication systems) creates a comprehensive protection system, significantly increasing the ability of organizations to counter modern complex cyber threats.
Additionally, the study found that XDR systems effectively detect hidden fileless attacks and rootkits, which traditionally pose
the greatest challenge for conventional defenses. Another important aspect is the ability of XDR solutions to reduce the number
of false positives through contextual analysis of events, which reduces the burden on security teams and increases the overall
efficiency of SOC operations. Despite the significant advantages of XDR, the study emphasizes that for full-fledged protection
of critical infrastructure, it is necessary to combine automated XDR solutions with deep expertise of DFIR specialists, especially
when analyzing new and unknown threats.
Keywords: XDR, EDR, CrowdStrike Falcon, Microsoft Defender, malware, memory forensics, LOLBINs, fileless
attacks, cybersecurity, integration of defense systems.

References
1. Check Point Research Reports Highest Increase of Global Cyber Attacks Seen in Last Two Years – a 30%
Increase in Q2 2024 Global Cyber Attacks. URL: https://blog.checkpoint.com/research/check-point-research-reportshighest-increase-of-global-cyber-attacks-seen-in-last-two-years-a-30-increase-in-q2-2024-global-cyber-attacks (дата
звернення: 10.05.2025).
2. Microsoft Digital Defense Report: 600 million cyberattacks per day around the globe. URL:
https://news.microsoft.com/en-cee/2024/11/29/microsoft-digital-defense-report-600-million-cyberattacks-per-dayaround-the-globe/ (дата звернення: 10.05.2025).
3. «XDR: The Evolution of Endpoint Security Solutions – Superior Extensibility and Analytics to Satisfy the
Organizational Needs of the Future» [Електронний ресурс]. Режим доступу: https://www.researchgate.net/ publication/
354190628 _ XDR _ The_ Evolution_ of_ Endpoint_ Security_ Solutions_ Superior_ Extensibility_ and_ Analytics_to_
Satisfy_the_Organizational_Needs_of_the_Future.
4. «Performance Evaluation of Open-Source Endpoint Detection and Response Combining Google Rapid
Response and Osquery for Threat Detection» [Електронний ресурс]. Режим доступу: https://www.researchgate.net/
publication / 358697816 _ Performance _Evaluation_of_Open-Source_Endpoint_Detection_and_Response_Combining_
Google_Rapid_Response_and_Osquery_for_Threat_Detection.
5. «Evolution of Endpoint Detection and Response (EDR) in Cyber Security: A Comprehensive Review»
[Електронний ресурс]. Режим доступу: https: // www.e3s-conferences.org / articles / e3sconf / pdf / 2024/86/e3sconf_
rawmu2024_01006.pdf.
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https://arxiv.org/html/2405.06124v1.
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antivirus-vs-edr-vs-xdr (дата звернення: 10.05.2025).
9. Extended Detection and Response (XDR). CrowdStrike. URL: https: // www.crowdstrike.com/en-us/cybersecurity-101/endpoint-security/extended-detection-and-response-xdr/ (дата звернення: 10.05.2025).
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com / en-us / azure / sentinel / microsoft-365-defender-sentinel-integration?tabs=defender-portal (дата звернення:
10.05.2025).
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https://www.malwarebytes.com/blog/news/2025/03/fake-captcha-websites-hijack-your-clipboard-to-install-informationstealers (дата звернення: 10.05.2025).
13. Fileless malware threats: Recent advances, analysis approach through memory forensics and research
challenges: [Електронний ресурс]. Режим доступу: https: // www.researchgate.net/publication/364769363_Fileless_
malware_threats_Recent_advances_analysis_approach_through_memory_forensics_and_research_challenges.
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com/r/Cortex-XDR/Cortex-XDR-Cloud-Documentation/IOC-rule-details.
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documentation/article/trend-vision-one-xdr-threat-investigation-whatsnew.
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/blog/product/perks-sigma-yara-edr/.
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github.io/posts/wmi-ad-enum/.
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content/dkim-spf-dmarc-explained/.
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jeffreyappel.nl/block-c2-communication-with-defender-for-endpoint/.
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INCREASING THE PRODUCTIVITY OF DECENTRALIZED DATABASES THROUGH OPTIMIZATION OF DATA FRAGMENTATION MECHANISMS IN BLOCKCHAIN NETWORKS

2025-06-28T17:48:43+00:00

The article presents a comprehensive methodology for optimizing the performance of decentralized databases based on
blockchain technology by implementing specialized data fragmentation mechanisms. The current issues of scalability of
distributed registries and the limitations of existing sharding approaches in the context of highly loaded systems are investigated.
An innovative hierarchical data fragmentation model using dynamic shards and adaptive load redistribution based on the
analysis of data access patterns is proposed. A mathematical model for optimizing the distribution of transactions between
shards is developed, taking into account the minimization of cross-sharding operations and balancing the computational load.
An original data structure based on modified prefix trees with vector labels is implemented for effective query routing in a
fragmented environment. The results of a comprehensive experimental study on a test bench with 64 nodes demonstrate an
increase in overall transaction throughput by 37-42% compared to traditional sharding approaches and a decrease in query
processing latency by 28% while maintaining the level of decentralization and cryptographic stability of the system. A
particularly significant improvement in performance (up to 60%) is observed for cross-sharding operations due to the
implementation of an optimized two-phase protocol with elements of batching and pre-validation. The proposed methodology
allows to effectively overcome the existing limitations of the "blockchain trilemma" by intelligently optimizing data structures
and consensus mechanisms, while maintaining the required level of security and decentralization of the system, which is
confirmed by resistance to a wide range of attacks even when a significant proportion of nodes in individual shards are
compromised. In addition to increasing performance, the developed methodology provides a number of additional advantages,
including: improved adaptability to changes in the nature of the load and data access patterns; reduced resource requirements of
individual network nodes due to effective distribution of computational load; increased resistance to attacks specific to sharding
architectures, such as "shard capture" and attacks aimed at violating the atomicity of cross-sharding transactions. The security
analysis demonstrates that the proposed model maintains a high level of protection even when up to 30% of nodes in the system
are compromised, while traditional sharding approaches demonstrate a critical decrease in stability already at 20-25% of
compromised nodes. The cost-effectiveness of the proposed methodology is confirmed by a 22-31% reduction in energy
consumption compared to existing solutions at the same level of performance, which makes it attractive for implementation in
corporate blockchain systems. The results obtained create the basis for further development of high-performance decentralized
data storage and processing systems capable of operating effectively under high loads while maintaining the key advantages of
blockchain technology in the context of transparency, integrity and data protection.
Keywords: data fragmentation, sharding, scalability, performance, blockchain trilemma, distributed ledgers, consensus
mechanisms, smart contracts.

References
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bitcoin.org/bitcoin.pdf.
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(2019). Forkbase: An Efficient Storage Engine for Blockchain and Forkable Applications. Proceedings of the VLDB
Endowment, 12(7), 764-777.
6. Wang, L., Shen, X., Li, J., Shao, J., & Yang, Y. (2019). Cryptographic primitives in blockchains. Journal of
Network and Computer Applications, 127, 43-58.
7. Zamani, M., Movahedi, M., & Raykova, M. (2018). RapidChain: Scaling Blockchain via Full Sharding.
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 931-948.
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(2020). Combining GHOST and Casper. ArXiv:2003.03052.
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for Analyzing Private Blockchains. Proceedings of the 2017 ACM International Conference on Management of Data,
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Scale-Out, Decentralized Ledger via Sharding. 2018 IEEE Symposium on Security and Privacy (SP), 583-598.
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COMPARATIVE STUDY OF VECTOR DATABASES BASED ON ANN FOR FAST AND ACCURATE FACE RECOGNITION IN DIGITAL FORENSICS

2025-06-28T17:48:50+00:00

The rapid growth of biometric data and the growing need for accurate face verification in the field of digital forensics
have necessitated the creation of scalable and efficient facial image search systems. This paper presents a comparative study of
five vector search algorithms — HNSW, Faiss, Annoy, PyNNDescent, and Nearest Neighbors — for face identification tasks
based on vector representations (embeddings). The experiment was designed taking into account conditions close to real forensic
scenarios, with a focus on such key evaluation metrics as Top-1 accuracy, similarity coefficient distribution, and query
processing time. All tested methods demonstrated high accuracy (over 91%), but significant differences were recorded between
them in terms of match confidence and speed. Faiss showed the highest similarity indicators, which indicates better search
accuracy, although it required significantly more computational resources. In contrast, the HNSW and PyNNDescent algorithms
provided near-instantaneous query processing with competitive accuracy, but with higher variability in the quality of results.
Annoy proved to be a compromise solution that combines high accuracy with low latency. The results highlight important tradeoffs between accuracy, confidence, and efficiency, providing valuable guidelines for selecting optimal vector search
technologies in facial recognition systems in forensics. In addition, the study proposed a reproducible benchmarking
methodology that can be used to further evaluate biometric search tools in law enforcement and security.
Keywords: vector search, facial recognition, digital forensics, HNSW, Faiss, Annoy, PyNNDescent, biometric
identification.

References
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https://doi.org/10.5281/zenodo.3528499.
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Hierarchical Navigable Small World graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4),
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METHOD OF DETECTING VULNERABILITIES AND AUTOMATED RESPONSE IN CORPORATE DATABASE PROTECTION SYSTEMS

2025-06-28T17:48:58+00:00

The article proposes a scientifically based method for detecting vulnerabilities and automated response in corporate
database protection systems operating in modern network infrastructure. The relevance of the study is due to the increasing
complexity of cyberattacks, the increase in data volumes, and the spread of cloud technologies, which significantly complicate
access control and make it impossible to use only traditional approaches to ensuring the security of database management
systems. A multi-level architecture is proposed, which is based on a combination of user behavior analysis models and
mathematical risk assessment of database queries. Each SQL query is described by a vector of features that are analyzed using
the Isolation Forest model. The determined threat level allows for the formation of a combined risk assessment that integrates
behavioral anomaly and query criticality. Based on this assessment, a real-time automatic response mechanism is implemented
- in particular, access blocking, SOC notification, and possible launch of scripts via a plug-in for the SIEM system. A feature of
the method is the possibility of its adaptation to real IT infrastructures, which is ensured by the modularity of the system and
compatibility with existing monitoring tools. The proposed method is an innovative combination of behavioral analysis, adaptive
machine learning and automated response in a single architecture for protecting corporate databases. Its distinctive features are
proactivity, flexibility of response, preventive action before executing a request and the possibility of integration with existing
SOC solutions. The effectiveness of the method is confirmed by the results of modeling, in particular by comparison with other
approaches using completeness metrics and ROC curves. The proposed solution has practical significance for increasing the
resilience of corporate database management systems to internal and external threats.
Keywords: information security, database protection, detection of access anomalies, response automation.

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