Machine learning technique detects phishing sites based on markup visualization

Machine learning models trained on the visual representation of website code can help improve the accuracy and speed of detecting phishing websites. This is according to a paper (PDF) by security researchers at the University of Plymouth and the University of Portsmouth, UK. The researchers aim to address the shortcomings of existing detection methods, which are either too slow or not accurate enough. The technique developed by the researchers uses "binary visualization" libraries to transform the markup and code of web pages into images. Using this method, they created a dataset of legitimate and phishing images of websites.