September 20, 2016 / Modified nov 29, 2016 3:50 p.m.

ASU Lab Tracking Cyber Threats On Deep Web, Dark Web

Machine learning and data mining aim to identify patterns to stop attacks before they occur.

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By Nicholas Gerbis, Arizona Science Desk

Rising cyberattacks threaten everything from medical records to critical infrastructure. Now a lab at Arizona State University is spotting hacker activity before cyberattacks occur.

The time to fix a security flaw is before it’s exploited — just ask the Clinton campaign or the World Anti-Doping Agency. So ASU’s Paulo Shakarian traces cyber threats to where they live: In the hard-to-access deep web and the secretive dark web.

The deep web are websites that "have special access restrictions that disallow Google and other search engines to index them," said Shakarian. “Likewise, there’s other sites that you need a special layer of secure software to anonymize your presence — one most common one is known as Tor — and these sites are collectively referred to as the dark web or dark net.”

The lab’s system, which uses machine learning and data mining to learn threat patterns, averages 305 cyber threat warnings each week.

“By understanding what the attackers are currently working on, we can better focus our resources to defend against what’s coming in the future," said Shakarian.

Arizona Science Desk
This story is from the Arizona Science Desk, a collaborative of the state's public radio stations, including NPR 89.1. Read more from the Arizona Science Desk.
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