Real-Time AI/ML-Based Phishing Detection and Prevention System

Abstract

Phishing attacks, which use phony emails, websites, and messages to trick users into disclosing private information like passwords or bank account information, have grown to be a significant cyber security concern. Phishing attacks are fraudulent attempts to obtain sensitive data by posing as a reliable individual or business. These attacks are growing more frequent and sophisticated. Antiquated phishing detection techniques that rely on set rules or recognized patterns frequently fall behind new phishing techniques. The potential of artificial intelligence (AI) to enhance phishing detection systems is discussed in this paper. AI detects and halts phishing more rapidly and precisely by using methods like machine learning, natural language processing, and pattern recognition. AI can identify subtle phishing indicators that traditional systems might overlook by analyzing vast volumes of data. The article also covers a variety of AI approaches, including deep learning, ensemble approaches, and supervised and unsupervised learning. It examines how well these AI systems function in practical settings and how well they adapt to novel phishing techniques. The study concludes by discussing the difficulties and potential advancements that will be required to address the ever-evolving and evolving phishing threats.