Tool to check malware in Twitter URLS

The system could identify potential cyberattacks with up to 83% accuracy within five seconds and with up to 98% accuracy within 30 seconds when a user clicked on a URL posted on Twitter and malware began to infect the device. 

"We are trying to build systems that can help law enforcement authorities make decisions in a changing cyber security landscape," said principal investigator on the project, professor Omer Rana. 


As people are increasingly using social networks such as Twitter to find information about events, the high volume of traffic around large-scale events creates a perfect environment for cyber-criminals to launch surreptitious attacks. 

The scientists collected tweets containing URLs during the 2015 Superbowl and cricket world cup finals, and monitored interactions between a website and a user's device to recognize the features of a malicious attack.