Researchers have created a scanner that flags URLs that are used for the fraudulent activity.

The rise of online banking, e-commerce, digital healthcare and other virtual activities has also led to an increased risk of data heists, financial scams and cheating via dubious platforms on the internet, while cyber security experts as well as agencies struggle to tackle them all. A sudden surge in digital activity and screen time during the pandemic has made ordinary netizens more vulnerable to fraudulent messages or emails, which are used as a ploy for extracting their personal details to swindle cash from bank accounts.

Phishing had taken off as a scam driven by phone calls made by people posing as representatives of banks, after which online portals and emails were used for approaching unsuspecting internet users to steal their sensitive information. With a view to preemptively crackdown against such schemes, a university in Qatar has created a scanner which can go through URLs, to predict which one has a higher risk of being associated with cyber crooks looking to trick netizens.

Developed by researchers at the Hamad Bin Khalifa University, the mechanism doesn't use local resources , and instead digs out global associations of every URL, in order to flag and block those which look dubious. It focuses on multiple IP addresses that host the same shady URLs, and a single IP which hosts different URLs of a similar nature, to detect patterns and links, that helps the system predict risks of phishing attacks from them.

Since cyber criminals continue to keep up with the surge in online data and transactions by coming up with new ploys from time to time, the researchers have created a smart and quick tool for analysis to gain an edge with predictions. The URLs that this solution aims to weed out, are ones that are capable of rendering a server unusable by triggering denial of service.

Over the past year, AI and predictive tech has also been incorporated into fintech apps in the Middle East, to highlight possible scams.