Enigma Enterprise
Machine learning with Enigma.
Leverage our machine learning program to create internal firewall rule sets and identify anomalies.
Zone based micro segmentation for compliance.
Internal network segmentation is a challenge.
It is a hard task to complete for organizations large and small.
However, organizations looking to comply with various regulation frameworks, such as the Cybersecurity Maturity Model Certification (CMMC) and NIST 800-171, need to meet certain standards for data segmentation and protection.
In order to properly attempt to create internal network segmentation you must have multiple full time resources and technologies.
Even with full time resources, it can be a very manual and time consuming process.
Requiring your staff to constantly baseline network traffic and updating network as new systems are introduced to your network.
Streamline your compliance efforts.
Enigma collects and analyzes your network data to build firewall rule sets.
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Our lightweight collector harvests only the meta data required to build FW rule sets and monitor for abnormal activity.
No sensitive PCI/PII data is collected.
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Our machine learning tool (Enigma ML) processes the data on a daily basis and begins to baseline your traffic and find patterns.
Learning what systems are talking to who and classifying systems based on protocols.
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Once we baseline your networks activity, we provide analytics that can be give directly to Firewall (FW) admins.
Allowing them to build and/or update your internal firewalls.
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After Enigma’s algorithms have identified patterns, Enigma begins to monitor for changes in activity.
These changes can be operational (a new systems was added to the network) or security related (a threat actor is inside).