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BluVector Awarded Additional Patent for Machine Learning in Cybersecurity

In-Situ Capabilities Deliver Moving Defenses for BluVector Customers

BluVector, a leader in AI-driven network security, announced that it has been issued a new patent for “System and method for in-situ classifier retraining for malware identification and model heterogeneity” (U.S. Patent 10,121,108).

BluVector issued patent for “System and method for in-situ classifier retraining for malware identification and model heterogeneity” (U.S. Patent 10,121,108). It marks the company’s third patent for #cybersecurity.

The recently awarded patent is the company’s third in machine learning for cybersecurity, supporting BluVector’s continued leadership in leveraging AI-based approaches to deal with the volume, velocity and polymorphic nature of cybersecurity threats.

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“This patent is another in a series of innovations we have brought to market to deliver highly scalable, real-time analysis of file-based and fileless threats,” said Dr. Scott Miserendino, VP R&D. “This patent specifically highlights our ability to retrain our machine learning models locally, producing defenses unique to each customer environment.”

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To date, BluVector has been issued three patents related to machine learning in cybersecurity and is the first and only network security vendor offering analytics specifically designed to detect fileless malware on the network. Through Speculative Code Execution, BluVector offers the greatest breadth of fileless malware coverage, including the detection of JavaScript-, VBScript- and PowerShell-based attacks. The analytic operates on any network stream at line speeds, emulating how fileless attacks will behave when executed.

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