CORRECTING and REPLACING PatternEx Announces the First Artificial Intelligence SaaS Application for Cyber Attack Detection at RSA Conference

CORRECTION...by PatternEx

SAN JOSE, Calif.--()--Please replace the release dated February 14, 2017 with the following corrected version due to multiple revisions.

The corrected release reads:

PATTERNEX ANNOUNCES THE FIRST ARTIFICIAL INTELLIGENCE SAAS APPLICATION FOR CYBER ATTACK DETECTION AT RSA CONFERENCE

PatternEx, the leader in Artificial Intelligence for information security, today announced the first Artificial Intelligence SaaS application for cyber attack detection. PatternEx’s flagship product, the PatternEx Threat Prediction Platform, is available as a SaaS application with a Free Trial period to selected customers. The announcement took place at the RSA Conference in San Francisco, CA.

“Now customers can simply point their Next-Gen Firewall logs to the cloud to detect Command and Control (C2) communications using Artificial Intelligence models. These models learn from analyst feedback, and automatically adapt to a given customer’s unique attack landscape-- without the need for a data scientist.” - Uday Veeramachaneni, PatternEx CEO.

The Artificial Intelligence SaaS application will include the following, for selected customers:

  • Free Trial period
  • Instant visibility into behaviors contained in existing NGFW logs
  • Active learning loop, incorporating human input in real time
  • Artificial Intelligence models tuned to detect C2 communications
  • Automatic model updates adapting to the evolving attack landscape

“CISOs are challenged with analyzing more data in real time with the inductive skill of an analyst, without having to hire more analysts. There is far too much data to be analyzed today and limited skills to do it, leaving enterprises a step behind the attackers. Artificial Intelligence offers the potential to close this gap.” - Latha Maripuri, Global CISO, News Corp.

Searching for IoC’s with a SIEM is a time consuming exercise that generates too many false positives to be effective. An Artificial Intelligence solution by contrast rolls up many log lines into a single behavior, then analyzes the behavior pattern utilizing human input, and automates the detection of that pattern in both historical data and as the attacks happen.

The PatternEx Threat Prediction Platform is a human-assisted Artificial Intelligence platform that detects cyberattacks in real time. This approach has been proven to produce five times fewer false positives while detecting ten times more attacks than anomaly detection solutions.

The heart of the PatternEx solution is technology known as “Active Contextual Modeling” or ACM, that synthesizes analyst intuition into predictive models. These models, when deployed across global customers, can learn from each other and achieve a network effect in detecting attack patterns.

PatternEx essentially creates “virtual security analysts” that mimic the intuition of human security analysts, providing InfoSec analyst teams with instant scale, and making existing analysts more efficient.

The Free Trial is generally available on February 14th, 2017. The Free Trial is restricted to detecting C2 communications from the logs of Next Gen Firewalls such as Palo Alto Networks and Fortinet. For a broader enterprise trial, spanning multiple use cases, contact us at sales@patternex.com.

To access the Free Trial of the Threat Prediction Platform, please visit www.patternex.com/freetrial

About PatternEx
PatternEx’s Threat Prediction Platform is changing the nature of Information Security. Powered by patent-pending Active Contextual Modeling technology, the Platform combines artificial intelligence and analyst intuition in a revolutionary methodology that teaches software to identify malicious behaviors in real time, at scale across the enterprise. PatternEx is headquartered in Silicon Valley.

For more information go to www.patternex.com

Contacts

For PatternEx:
Carly Martinetti
carly@pressfriendly.com

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Contacts

For PatternEx:
Carly Martinetti
carly@pressfriendly.com