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Adaptive Security Engine
(ASE), is a breakthrough security information analysis
technology that automates the analysis and origination of
actionable intelligence from the voluminous logs and reports
generated by the array of security solutions deployed across
the enterprise. ASE overcomes the limitations of policy,
signature and rules-based approaches and represents a major
advancement in anomaly detection that successfully addresses
its two most commonly cited limitations: accuracy and
adaptivity.
ASE is available to security
technology companies and solutions providers looking to
enhance and differentiate their offerings in response to
growing customer demand for intelligent, adaptive solutions
that automate some of today's manual security administrative
functions. ASE is being integrated into some of the industry's
leading network monitoring, threat prevention, and security
information management solutions.
ASE automatically sifts
through and analyzes the high-volume output produced by
network and security products to instantaneously identify the
most serious risks, misuse and vulnerabilities that threaten
the enterprise. The traditional time consuming, error prone
and labor-intensive process assigned to system administrators
can now be fully automated and reduced to minutes or less.
This frees up security staff to focus on more highly valued
and important tasks such as responding sooner to the most
serious breaches and initiating the appropriate defensive and
preventative actions.
ASE generates more accurate
results and reduces the number of false alerts by doing a
better job of distinguishing between threatening and
non-threatening security events. As it formulates more precise
event categorizations, ASE is simultaneously adapting its
perspective of normal and suspicious events as it takes into
account the dynamic nature of the environment it is
monitoring.
The keys to achieving these
performance advantages are in the data and processing models
that underpin the Adaptive Security Engine:
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Open and heterogeneous
data model incorporates data from the wide array of
currently available security technologies in unlimited
combinations
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Fuzzy clustering allows
for continual processing of large volumes of multivariate
structures
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Kernel mode classifiers
allow events to be automatically and precisely categorized
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Unsupervised learning
technology draws from accumulated experiences, knowledge
and changes in the environment to drive self-adaptiveness
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User interface fosters
supervised learning derived from the know-how and
experiences of expert administrators
To learn
more about ASE technology, OEM and other licensing
opportunities, or to schedule a demonstration, contact a PWI
representative today.
partners@pwicorp.com, 732-212-8110 x235
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