Anti Phishing

Anti-phishing research aims to develop robust and efficient methods for detecting and preventing phishing attacks, which exploit social engineering to steal sensitive user information. Current efforts focus on leveraging machine learning, particularly deep learning models like transformers (e.g., BERT, DeBERTa) and recurrent neural networks (LSTMs), along with multimodal approaches integrating text, image, and audio analysis, to identify phishing websites, emails, and URLs. These advancements are crucial for enhancing cybersecurity, improving the accuracy and speed of phishing detection, and mitigating the significant financial and reputational damage caused by these attacks.