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BluVector and UMBC Partner to Advance Cyber Threat Detection and Response in University Environments

Partnership Introduces Students to the Latest Network Intrusion Detection System Technology and Supports the University’s Initiatives to Develop the Next Generation of Cybersecurity Talent

October 30, 2017 – Arlington, VA – BluVector, a leader in machine learning-based network intrusion detection, is partnering with the University of Maryland, Baltimore County (UMBC) to help build the newest generation of cybersecurity analysts. A team of students within the College of Engineering and Information Technology will now be using a version of BluVector to analyze the university’s network traffic in real time. The goal is to better understand how to find, confirm and contain cyber threats using advanced analytics, including supervised machine learning, speculative emulation and behavioral heuristics.

Cyber threat detection and response within an academic environment is challenging as IT departments often have less rigid control over devices on the network yet are tasked with supporting a vast variety of endpoints. By utilizing BluVector’s network intrusion system, students participating in the UMBC program will gain real world experience using deep analysis and detection to triage malicious events for either automated response actions or higher-level human investigation. It’s experience that will make them perfectly suited to operate as Level 1 analysts and highly sought after by future employers.

“At BluVector, learning is in the DNA of our team and our product,” said Robert Thompson, BluVector’s liaison to UMBC and a recent graduate of the Cyber Scholars program at the University. “A partnership with UMBC enables hands-on learning for students and we hope we can, in turn, learn from the students as they observe BluVector in a specialized environment.”

“We’re pleased to incorporate BluVector into the ecosystem UMBC has built to develop the next generation of cybersecurity talent,” said Dr. Charles Nicholas, professor of computer science and electrical engineering, UMBC and faculty advisor for UMBC’s Cyber Dawgs, its 2017 National Collegiate Cyber Defense Championship winning Cyber Defense Team. “We hope exposure to analytics driven advanced threat detection solutions both sparks curiosity in data science and underscores the value of machine learning among our students as they enter the workforce to tackle the emerging and dynamic cyber threats we all face.”

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