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Open Source Innovation Strengthens Cloudera's Cybersecurity Solution

  • Tuesday, July 25, 2017, 8:18 am
  • ACROFAN=Yong-Man Kwon
  • yongman.kwon@acrofan.com
Cloudera announced the availability of Apache Spot 1.0 (incubating), which enables fast, easy, and more scaleable cybersecurity machine learning. Spot is a community-driven cybersecurity project, built to bring advanced analytics to all IT Telemetry data on an open, scalable platform.

Since Cloudera's cybersecurity solution is built on Spot, this open source release strengthens the solution allowing enterprises to more effectively accelerate advanced threat detection at scale. Spot provides a community based approach to cybersecurity allowing organizations to collaborate across industries while simultaneously changing the economics of cybersecurity.

The Spot open source project delivers visibility into security threats by providing advanced threat detection using machine learning and advanced analytics. Spot is built on top of Cloudera's platform leveraging Apache Spark and Hadoop, optimized for Intel hardware, and provides the ability to ingest and store high volumes of IT telemetry data for advanced threat detection with machine learning, accelerated threat investigation with complete contextual information at analyst finger tips, and a future-proofed open source infrastructure that changes the economics of cybersecurity.

Highlights from the Spot 1.0 release (incubating) include:

Improved machine learning performance with Spot's upgrade to Apache Spark 2.1.
Better run times and model performance for all DNS, proxy, and NetFlow workloads due to improvements to the Suspicious Connects open source machine learning models.
Tighter integration with Cloudera's platform to take advantage of Cloudera components while enhancing the Apache Spot open data model.

Cloudera's cybersecurity solution, built on Apache Spot, uses advanced machine learning to baseline normal enterprise behavior across networks, endpoints, and users in order to see anomalies within the enterprise. Creating a single pane of glass for complete contextual security data allows for organizations to store multiple years worth of data at a lower cost while accelerating threat investigation and response.

As cybersecurity threats become more mature and unique, organizations are in need of an open source approach to extend enterprise visibility while laying the foundation for advanced machine learning threat detection.