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Cracking down on crime with AI | Qatar University

Cracking down on crime with AI

2021-03-22 00:00:00.0
Cybercrime,,Hacking,And,Technology,Crime.,No,Face,Hacker,With,Laptop

The Problem

As our society grows more digitally sophisticated, so too do cyber criminals. Cybersecurity has become an increasingly important issue in the 21st century as hackers target governments, businesses and individuals all over the world. Attacks from hackers are virtually constant, with one every 39 seconds, according to a study by the University of Maryland. And the damage they cause is huge. A report from global security advisory specialists the Herjavec Group predicts that cybercrime will cost the world $6 trillion (£5.2 trillion) annually by 2021. Recent examples include the hacking of hotel chain Marriott International in 2018, during which private data was stolen from up to 383 million customers, including passport and credit card information. In 2017, an attack on Qatar News Agency also highlighted the risk cybercrime poses to the national security of nations.

The solution

But even as hackers develop more complex and cunning ways to launch attacks, others are fighting back. Researchers at Qatar University are using AI to expose the cyber criminals lurking in the virtual shadows. Somaya Al-Maadeed, head of the computer science and engineering department at Qatar University, received more than $5 million grants for research related to image processing and artificial intelligence. One of the latest project she led is a project uncovering criminals’ hidden online messages.

“Criminals can communicate via messages hidden within YouTube for example, or Facebook or another app,” she explains. “They can hide messages, documents and data in an image or video. So, it is not easy to detect and it is a very serious problem.”

The researchers have developed a system – the first stage of which has a patent pending – to use AI and machine learning to detect these criminal communications. Using existing examples, a trainer “teaches” a computer what to look for, to the point where it can predict which content has hidden messages embedded within it. Learn more

Name of the researcher: Somaya Al-maadeed

Head of Computer Science and Engineering