Machine learning based tool to analyze if a URL is safe to click.
Should I Click is a free online service that uses machine learning to analyze and identify if a URL is safe to click. By providing this web service to the general public we hope to help protect the civil society and reduce the number of successful attacks. This expected impact is in line with our long-term goal defined by the Civilsphere project. After recent discovery of Geost Botnet and publishing a dataset of valuable IoT traffic for research purposes, this is another great (and very tangible) research output of our cybersecurity lab. The main researcher behind this tool is František Střasák, who is no longer part of our team (good luck Frenky on your next career path, you will be missed).
How does Should I Click work
The program uses machine learning systems that were trained with thousands of real attack pages. As a user you simply put the link on the web page and it will let you know how safe it is to click on it. Moreover, it will tell you why it is not safe and it will allow you to give feedback. This service was born with the aim of protecting the civil society, journalists, activists, and people at risk from targeted attacks. Maybe you ask yourself why current anti-virus softwares are not enough to notify you about dangerous websites. Phishing links are very hard to detect and current technologies rely on blacklists and whitelists to stop this type of malicious websites. The problem of these approaches is that they need to already know about a malicious website to include it on the blacklist. In this way, new phishing websites are not blocked and users keep being at risk. Anti-virus, web browsers, and script blockers all aim to warn and sometimes block certain behavior but not completely, and they always fail to detect new techniques and attacks. Should I Click analysis any website, even new ones, and is capable of detecting new and unknown risks.
Do you wonder, which websites are mostly detected as dangerous? Read more about Should I Click on the project's website.