Classifying Phishing URLs Using Recurrent Neural Networks

Classifying Phishing URLs Using Recurrent Neural Networks

4 In a recent research paper, we showed how we are able to detect with a high level of accuracy if a website is a phish just by looking at the URL. This post lays out in greater detail how, by using a deep recurrent neural network, we’re able to accurately classify more than 98 percent of URLs.

Phishing attacks are a growing problem worldwide. According to the Anti-Phishing Working Group (APWG), the number of phishing websites increased by 250 percent during the last quarter of 2015 and the first quarter of 2016, targeting more than 400 brands each month, the most APWG has seen since it began tracking and reporting on phishing in 2004. The use of phishing by a criminal is focused on using social engineering schemes to steal consumers’ personal and financial information. The attacks are designed to trick consumers into giving financial data–such as usernames and passwords–to fake websites purporting to be legitimate businesses. [Read More]