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DNSFilter Named Winner of 2022 Black Unicorn Awards
by DNSFilter Team on Nov 1, 2022 12:00:00 AM
DNSFilter today announced it has been named a winner of the 2022 Black Unicorn Awards. The company was recognized as a Top 10 Baby Black Unicorn Award Winner for 2022, which honors cybersecurity companies predicted to be worth $1 billion dollar market value in three to five years.
DNSFilter is redefining how organizations secure the DNS layer with ML-powered DNS threat protection that uniquely identifies 61% of threats in-house. DNSFilter catches more zero-day attacks in process than competitors, identifying compromised domains an average of 7 days before they appear on other external threat feeds. DNSFilter has experienced a 94% increase in ARR in 2022 because more IT professionals are waking up to the importance of deploying a first-line-of-defense at the DNS layer, with the ability to identify and block end user exposure to phishing, malware, and advanced cyber threats that come from malicious domains.
“Our mission is to change the way people think about security at the DNS layer,” said Ken Carnesi, CEO and Co-founder, DNSFilter. “By resolving the inefficiencies found within legacy solutions, we’re making threat protection and content filtering simple and easy. Surpassing 94% growth in ARR over the past year validates the value of our unique ability to identify previously unseen threats, and we look forward to taking DNS security to places it’s never been before.”
This recognition comes on the heels of DNSFilter being named a winner of the 2022 SINET16 Innovator Award and 2022 Cybersecurity Breakthrough Awards. The company’s ability to categorize domains in real-time and automatically block new, potentially dangerous domains enables DNSFilter to deliver best-in-class data efficacy, UI, features, and usability.
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Host Dave Sobel sits down with Ken Carnesi, the co-founder and CEO of DNSFilter, to explore the integration of artificial intelligence (AI) within their DNS security solutions. Ken explains how DNSFilter leverages machine learning to enhance threat intelligence by analyzing both proprietary data and third-party feeds. With over 100 different feeds, the challenge lies in reconciling differing opinions on what constitutes a threat. By employing mac...
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