INTELLIGENT CYBER DEFENCE SYSTEMS: DETECTION OF RANSOMWARE AND PROTECTION OF WIRELESS NETWORKS BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES


Oleh Harasymchuk; Ivan Opirskyy, Roman Banakh, Danyil Zhuravchak, Olha Partyka, Elena Nyemkova, Sviatoslav Vasylyshyn, Andrii Partyka, Yuriy Nakonechnyy, Taras Lukovskyy, Vitalii Susukailo, Viktor Otenko, Ivan Tyshyk, Nazarii Dzianyi, Dmytro Sabodashko, Petro Haraniuk, Valerii Dudykevych, Serhiy Semenyuk, Marta Stakhiv, Ihor Zhuravel, Taras Kret, Lesya Mychuda, Zynoviy Mychuda, Orest Polotai, Yevhenii Kurii, Nataliya Nakonechna, Nataliya Luzhetska, Anatoliy Obshta, Tetiana Korobeinikova

The monograph is devoted to a comprehensive study of two critical areas of cybersecurity: countering ransomware and protecting IEEE 802.11 wireless networks. The work combines theoretical research and practical solutions for creating effective information security systems.

The first part of the monograph explores methods for detecting and countering ransomware viruses in real time using eBPF technology and machine learning models. An innovative model of an integrated data collection system is presented, combining monitoring of system calls, file and cryptographic activity with network traffic analysis. A comprehensive classification model based on an ensemble of decision trees and random forests is proposed, demonstrating malware detection accuracy above 95%. A methodology for applying deep neural networks to identify complex ransomware behaviour patterns has been developed, providing 97.8% identification accuracy.

The second part of the work is devoted to the development of innovative approaches to protecting wireless Wi-Fi networks. A conceptual model of the Wireless Honeypot as a Service information protection system using cloud computing is presented, which provides improved speed and deployment flexibility. A unique method for tracking attackers based on metadata with 90–100% geolocation accuracy has been developed. A diagnostic model of a decoy system has been proposed, which allows configurations to be automatically generated according to the attacker’s profile. A method for detecting intrusions based on the K-nearest neighbours algorithm has been presented, which provides 100% accuracy in detecting ‘evil twin’ attacks.
The practical value of the monograph lies in the possibility of directly implementing the developed methods and tools in cybersecurity systems. The research results can be used to protect both corporate and private networks. The proposed solutions significantly increase the level of protection against modern cyber threats, including ransomware and attacks on wireless networks.

The monograph will be useful for cybersecurity specialists, system administrators, software developers, researchers, teachers, and students of relevant specialities. The materials of the work are also of interest to managers of organisations and specialists responsible for the information security of enterprises of various forms of ownership.

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How to cite paper:

Harasymchuk, O. (Ed.) (2025). Intelligent cyber defence systems: detection of ransomware and
protection of wireless networks based on artificial intelligence technologies: collective monograph. Kharkiv:
ТЕСHNOLOGY СЕNTЕR PC, 132. doi: http://doi.org/10.15587/978-617-8360-22-1