DHS, CISA Building AI-Based Cybersecurity Analytics Sandbox

Two of the US government's leading security agencies are building a machine learning-based analytics environment to defend against rapidly evolving threats and create more resilient infrastructures for both government entities and private organizations. From a report: The Department of Homeland Security (DHS) -- in particular its Science and Technology Directorate research arm -- and Cybersecurity and Infrastructure Security Agency (CISA) picture a multicloud collaborative sandbox that will become a training ground for government boffins to test analytic methods and technologies that rely heavily on artificial intelligence and machine learning techniques. It also will include an automated machine learning "loop" through which workloads -- think exporting and tuning data -- will flow. The CISA Advanced Analytics Platform for Machine Learning (CAP-M) -- previously known as CyLab -- will drive problem solving around cybersecurity that encompasses both on-premises and cloud environments, according to the agencies. "Fully realized, CAP-M will feature a multi-cloud environment and multiple data structures, a logical data warehouse to facilitate access across CISA data sets, and a production-like environment to enable realistic testing of vendor solutions," DHS and CISA wrote in a one-page description of the project. "While initially supporting cyber missions, this environment will be flexible and extensible to support data sets, tools, and collaboration for other infrastructure security missions."

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