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Tuesday, Dec 6, 2016


Developing Cyber Attack Prediction Capability for IARPA

  • Researchers will create new technology to predict threats and provide timely warnings.

The U.S. Intelligence Advanced Research Projects Activity (IARPA) has selected BAE Systems to develop technology that will help the U.S. military and intelligence agencies forecast and detect cyber-attacks significantly earlier than existing methods allow. The approximate lifetime value of the contract is $11.4 million.

Current cyber defense methods typically react to attacks already underway or completed. IARPA's Cyber-attack Automated Unconventional Sensor Environment (CAUSE) program aims to create new technology that will accurately predict threats and automatically provide timely warnings of cyber threats against participating organizations, allowing for defensive actions ahead of an attack. BAE Systems will develop new predictive methods that combine existing advanced intrusion detection capabilities with unconventional publicly available data sources, leveraging sources not usually associated with cybersecurity. Researchers will seek to identify leading indicators of an attack from vast, noisy external streams of data and then correlate related data from different sources to generate accurate, actionable warnings.

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"This award builds on our expertise in cybersecurity and multi-intelligence sensor data fusion technologies, including the areas of machine learning, event detection, correlation, and prediction," said Anne Taylor, who directs the Cyber and Communications Technologies Research group at BAE Systems. "Our team will also provide insight into adversary motivations and actions, which will enhance our prediction models."

The company's teammates on the program include StratumPoint, Digital Operatives LLC, and University of Maryland professor David Maimon. BAE Systems' work will be based at its facility in Arlington, Virginia.

Source : BAE Systems PLC (LSE: BAES.L) - view original press release

Published on ASDNews: Oct 13, 2016

 

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