Title: Artificial Intelligence-Based Systems For Cyberattack Detection And Prevention
Authors: Kalmuratov Makset Tajimuratovich
Volume: 10
Issue: 6
Pages: 308-311
Publication Date: 2026/06/28
Abstract:
The rise of cyberattacks has made traditional cybersecurity methods less effective against evolving threats. This study explores artificial intelligence-based systems for cyberattack detection and prevention, focusing on their efficiency and practical advantages. Using a qualitative review of recent literature, the research shows that machine learning and deep learning significantly improve threat detection accuracy, reduce response time, and enable automated defense mechanisms. AI systems are also effective in identifying both known and unknown attacks through anomaly detection and predictive analytics. However, challenges such as data quality, high computational cost, and adversarial manipulation remain. Overall, the study confirms that artificial intelligence plays a key role in strengthening modern cybersecurity systems.