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Machine learning from ‘baby unicorn’ DNSFilter targets zero day attacks

Network security has taken another step forward by incorporating machine learning at the DNS layer, according to vendor DNSFilter.

Ken Carnesi, chief executive officer and co-founder at DNSFilter, said that by resolving the inefficiencies found within legacy solutions, it had simplified threat protection and content filtering

The approach has netted the growing solution provider a top-10 place in the Cyber Defense Baby Black Unicorn Awards for 2022.

“Our mission is to change the way people think about security at the DNS layer,” Carnesi said in the announcement.

DNSFilter incorporates machine learning in its DNS threat protection, which it says means it can identify around 61% of threats in-house, and more zero-day attacks in progress than competitors.

The company said it can identify compromised domains an average of seven days before they appear on other external threat feeds, deploying a first line of defence at the DNS layer that could both identify and block end user exposure to phishing, malware and advanced cyber threats.

The Top 10 Baby Black Unicorn Award Winner for 2022 prize aims to spotlight cybersecurity companies with the potential to become worth $1 billion in market value in three to five years, the company said.

DNSFilter has also won a 2022 SINET16 Innovator Award and at the 2022 Cybersecurity Breakthrough Awards.

“The company’s ability to categorise domains in real-time and automatically block new, potentially dangerous domains enables DNSFilter to deliver best-in-class data efficacy, UI, features, and usability,” the company said.

The DNSFilter technology is already being used by the likes of Germany-based Frederix Hotspot, which has singled out its global block policies as a “real blessing” for customers.

( Image by JL G from Pixabay  )

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