AI-Enhanced Cybersecurity: Deep Learning Phishing Detection Methods

Abstract

Because cyber attacks are constantly evolving to become more sophisticated, it is more crucial than ever to have state-of-the-art cybersecurity solutions in place. Phishing attempts are very risky for businesses and individuals alike because they can lead to data breaches and financial losses. enhancing phishing detection skills by the use of deep learning techniques inside the realm of artificial intelligence (AI). In this study, we look at how well convolutional neural networks (CNNs) and recurrent neural networks (RNNs) analyze patterns in email content, URLs, and user activity to identify potential phishing attempts. Thru analysis of various topologies and performance metrics, this study demonstrates that deep learning architectures provide better detection rates than conventional methods. Data quality, model interpretability, and the need for continuous learning to tackle evolving phishing tactics are additional challenges. Results suggest that deep learning is a potent technique with the potential to enhance phishing detection systems, providing further security to businesses from fraudsters.  Artificial intelligence (AI) can protect sensitive data from phishing attacks and substantially enhance cybersecurity frameworks.