Cybersecurity researchers from Deutsche Telekom’s innovation lab at Ben-Gurion University in Beersheba have discovered and traced six “botnet” hacking programs by analyzing data collected from past cyber-attacks. The breakthrough research may be of great importance to law enforcement agencies and cyber-security specialists around the world.
“In this project,” explained Ariel Bar, one of the lead researchers on the team, “we implemented a number of unique advanced algorithms based on machine learning in order to reach the important outcomes that we achieved.”
Botnets are networks of malicious remotely updatable code that lurk on infected computers unbeknownst to their owners. Using botnets, hackers and cyber-criminals can carry out powerful attacks that, until now, were largely untraceable.
A team led by Profs. Bracha Shapira and Lior Rokach analyzed data captured by a “honeypot” network run by Deutsche Telekom, one of the world’s leading telecommunications companies. The team was able to identify six separate botnets, each capable of inflicting serious criminal and monetary damage.
By analyzing the data, the team built a breakthrough program that identifies the botnet by finding similar attack patterns. Law enforcement can then track the botnet back to its administrator.
“This is the first time such a comprehensive study has been carried out and returned with unique findings,” said Dudu Mimran, Chief Technology officer of Deutsche Telekom Innovation [email protected] “In addition to the aforementioned findings, there were other interesting achievements. For example, the ability to identify whether the attack emanated from a real person or from a robot, as well as the ability to predict future attacks.”
Deutsche Telekom Innovation [email protected] is a unique research lab staffed largely by faculty and students at Ben-Gurion University, who conduct cutting-edge cyber security research on behalf of Deutsche Telekom. Shapira, Rokach and Elovici are all members of BGU’s Department of Information Systems Engineering.
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