DOI:
https://doi.org/10.71337/inlibrary.uz.science-research.139161Keywords:
artificial intelligence phishing malware neural networks cybersecurity machine learning.Abstract
The growing challenge of phishing and malware attacks highlights the urgent need for intelligent early detection mechanisms. This article explores the application of artificial intelligence (AI), particularly neural networks, for identifying phishing messages, malicious files, and suspicious network traffic. The study focuses on the effectiveness of Convolutional (CNN) and Recurrent (RNN, LSTM) neural networks. The results show that AI-based systems can achieve over 95% accuracy in early threat detection.References
Goodfellow I., Bengio Y., Courville A. Deep Learning. MIT Press, 2016.
Sahu R., Jena S.K. AI-Based Phishing Detection Techniques: A Review. Journal of Information Security, 2021.
Zhang J. et al. CNN-LSTM Hybrid Models for Malware Detection, IEEE Access, 2022.
O‘zbekiston Respublikasi Axborot texnologiyalari va kommunikatsiyalarini rivojlantirish vazirligi. Kiberxavfsizlik konsepsiyasi, 2023.
Alshamrani A. AI-Driven Cybersecurity: Challenges and Trends, Computers & Security, 2024.
