Open Source Innovation Strengthens Cloudera’s
Cybersecurity Solution and Accelerates Machine Learning at Scale
Cybersecurity Solution and Accelerates Machine Learning at Scale
Apache Spot (incubating), the community
fighting cyber threats, releases Spot 1.0 as they progress towards Apache
Software Foundation graduation
fighting cyber threats, releases Spot 1.0 as they progress towards Apache
Software Foundation graduation
SINGAPORE – July25, 2017 – Cloudera, (NYSE: CLDR), the leading provider of the modern
platform for machine learning and advanced analytics, announced the
availability of Apache Spot 1.0 (incubating), which enables fast, easy, and
more scalable 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.
“Taking advantage of
community based open source innovation and collaboration to strengthen our
solutions and deliver customer value is at the heart of Cloudera’s strategy,”
said Tom Reilly, chief executive officer at Cloudera. “With the release of Spot
1.0, we are excited to deliver a community-developed platform with which
enterprises can protect themselves and collaborate with peer organizations in
detecting cyber attacks in the hyper-connected world they operate in.”
community based open source innovation and collaboration to strengthen our
solutions and deliver customer value is at the heart of Cloudera’s strategy,”
said Tom Reilly, chief executive officer at Cloudera. “With the release of Spot
1.0, we are excited to deliver a community-developed platform with which
enterprises can protect themselves and collaborate with peer organizations in
detecting cyber attacks in the hyper-connected world they operate in.”
Cloudera Plus Apache
Spot Power Machine Learning Cybersecurity Applications
Spot Power Machine Learning Cybersecurity Applications
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.
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:
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.
“It is difficult for
cybersecurity teams across enterprises to collaborate when it comes to sharing
threat intelligence and acting upon it. Spot is a platform designed to
facilitate such collaboration starting with a shared common data model against
which community developed machine learning algorithms can be run,” said Sam
Heywood, director of Cybersecurity Strategy at Cloudera. “While threat
intelligence feeds are extremely important in the fight against cyber
criminals, we need to extend our analytics sharing capabilities to make sure we
are detecting advanced behavioral anomalies. Apache Spot is an award winning
technology community and project that is doing just that. Cloudera is playing
its role by helping organizations take advantage of the open source project
while making it easier to secure, manage, and scale community innovation in the
cloud or on-premises.”
cybersecurity teams across enterprises to collaborate when it comes to sharing
threat intelligence and acting upon it. Spot is a platform designed to
facilitate such collaboration starting with a shared common data model against
which community developed machine learning algorithms can be run,” said Sam
Heywood, director of Cybersecurity Strategy at Cloudera. “While threat
intelligence feeds are extremely important in the fight against cyber
criminals, we need to extend our analytics sharing capabilities to make sure we
are detecting advanced behavioral anomalies. Apache Spot is an award winning
technology community and project that is doing just that. Cloudera is playing
its role by helping organizations take advantage of the open source project
while making it easier to secure, manage, and scale community innovation in the
cloud or on-premises.”
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.
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.
By joining the Apache
Spot community, Cybraics, a leader in applying AI techniques to cybersecurity,
can access and share information to help push in this line, advancements into
the open source community and at the same time deliver results to their
customers in less time,” said Alan Ross, CTO Cybraics and Apache Spot Founder.
“As a contributor to Apache Spot, Cybraics will be sharing new analytics with
the community.”
Spot community, Cybraics, a leader in applying AI techniques to cybersecurity,
can access and share information to help push in this line, advancements into
the open source community and at the same time deliver results to their
customers in less time,” said Alan Ross, CTO Cybraics and Apache Spot Founder.
“As a contributor to Apache Spot, Cybraics will be sharing new analytics with
the community.”
About Cloudera
Cloudera delivers the modern platform for machine learning and advanced
analytics built on the latest open source technologies. The world’s
leading organizations trust Cloudera to help solve their most challenging
business problems by efficiently capturing, storing, processing and analyzing
vast amounts of data. Learn more at cloudera.com.
analytics built on the latest open source technologies. The world’s
leading organizations trust Cloudera to help solve their most challenging
business problems by efficiently capturing, storing, processing and analyzing
vast amounts of data. Learn more at cloudera.com.
Connect with Cloudera
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This
press release contains forward-looking statements including, among other
things, statements regarding the expected performance and benefits of
Cloudera’s offerings. The words “believe,” “may,”
“will,” “plan,” “expect,” and similar expressions
are intended to identify forward-looking statements. These forward-looking
statements are subject to risks, uncertainties, and assumptions. If the risks
materialize or assumptions prove incorrect, actual results could differ
materially from the results implied by these forward-looking statements. Risks
include, but are not limited to, risks described in our filings with the
Securities and Exchange Commission (SEC), including our Form S-1 Registration
Statement, and our future reports that we may file with the SEC from time to
time, which could cause actual results to vary from expectations. Cloudera
assumes no obligation to, and does not currently intend to, update any such
forward-looking statements after the date of this release.
press release contains forward-looking statements including, among other
things, statements regarding the expected performance and benefits of
Cloudera’s offerings. The words “believe,” “may,”
“will,” “plan,” “expect,” and similar expressions
are intended to identify forward-looking statements. These forward-looking
statements are subject to risks, uncertainties, and assumptions. If the risks
materialize or assumptions prove incorrect, actual results could differ
materially from the results implied by these forward-looking statements. Risks
include, but are not limited to, risks described in our filings with the
Securities and Exchange Commission (SEC), including our Form S-1 Registration
Statement, and our future reports that we may file with the SEC from time to
time, which could cause actual results to vary from expectations. Cloudera
assumes no obligation to, and does not currently intend to, update any such
forward-looking statements after the date of this release.
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