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CounterFlow AI Sponsors the Argus Project

January 13, 2020

Network visibility provider will be the first to commercially integrate Argus with its AI platform

CounterFlow AI, an AI-driven network visibility solutions firm, today announced its sponsorship of the Open Argus Project. As part of a broader agreement, CounterFlow AI will become the Project’s first commercial sponsor, contributing technology to the Argus open source network flow system, in addition to licensing the technology and integrating it with its ThreatEye platform.

Argus is a privately funded open source project focused on proof of concept innovations in network flow data. U.S. government agencies, including the U.S. Department of Defense, along with federally funded R&D centers, universities and corporations have turned to Argus to help understand and protect their increasingly complex networks. With this new sponsorship, Argus users will now have access to commercial technology contributions from CounterFlow AI.

“Its rich sets of well-structured telemetry data enable our streaming machine learning engine to detect network anomalies and threats in real-time. The type of features that Argus generates is a data scientist’s dream. For this reason, Argus is a logical choice for integrating with CounterFlow AI’s ThreatEye platform,” said Randy Caldejon, co-founder, CEO, CounterFlow AI. “This powerful combination will give organizations the capabilities necessary to understand what’s happening on their network in this encrypt-everything era.”

Nearly 80 percent1 of enterprises’ network traffic today is encrypted presenting analysts with a significant detection hurdle. Encrypted network traffic makes the decades-old deep packet inspection approach for detecting anomalies nearly inoperative. The alternative is deep packet dynamics - applying machine learning on contextual flow data to evaluate attributes of network traffic leading to quicker identification of malicious behavior and indicators of compromise. Access to larger swaths of well-structured network data is necessary to augment machine learning model development. Argus possesses 145 attributes covering network identification, services, resource utilization, packet dynamics, network activity metadata and content - providing CounterFlow AI’s machine learning engine with a rich set of network flow data.

“Machine learning is a perfect fit for analyzing large sets of network flow data, and the best results will come from analyzing the best network data available. This is now on an accelerated path thanks to CounterFlow AI’s commercial sponsorship,” said Carter Bullard, creator of Argus. “We look forward to CounterFlow AI’s contributions and seeing Argus users use machine learning more intelligently.”

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