Defending the Digital Frontier: URL-Based Phishing Detection Extension

The internet’s rapid expansion has led to an increase in cyberattacks and phishing schemes that rely on uniform resource location (URL) links. In today’s digital landscape, it’s vital to identify these harmful links for safety. Traditional methods struggle to adapt to new website URLs, so machine learning is being used to detect malicious URLs. Previous studies have explored various machine learning techniques for URL detection, but a recurring issue is the need to preprocess website links before analysis. To address this problem, a new neural network method has been introduced. This innovative approach enables the creation of a model capable of identifying malicious URLs without the need for repetitive feature extraction steps. This groundbreaking technique has shown impressive results in detecting dangerous web addresses, operating swiftly and accurately with a detection rate of 99.61%. This represents a significant advancement in the field of cybersecurity, offering an effective solution to the ever-evolving threat landscape posed by malicious URLs on the internet.