Network defense

CyberNeuro-RT

An IoT, AI/ML-driven, highly-scalable, real-time network defense and threat intelligence tool with CPU, GPU or low-power neuromorphic chip deployment.

6ML algorithm ensemble

75×dataset growth in under 2 months

2neuromorphic offerings, Intel and Brainchip

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Luminous traffic moving along filaments of a dark network

How it works

Cutting-edge unsupervised ML.

How CyberNeuro-RT detects, what it trains on, where it runs, and how it presents what it finds.

S01

Cutting-Edge Unsupervised ML

Scalable Unsupervised Outlier Detection (SUOD)

6 ML algorithm ensemble

Model approximation for complex models

Variational Autoencoder (VAE), trained to minimize reconstruction error of initial input and reconstructed output

S02

Proprietary Pipeline Adapts to Any Dataset

75x dataset growth in under 2 months.

Existing dataset ingestion: proprietary system enables ingestion of any existing network capture dataset with flexible support for any labelling system

From-the-wild zero day sampling: system enables capturing and simulation of novel threats for additional data sampling

Data generation via simulation: ThreatATI database and proprietary ingestion system enable sampling and augmentation for cataloged threats from proprietary and public threat databases

Follow threats home with dark web tracking

S03

At-the-edge Neuromorphic Processing

Two offerings from the leading neuromorphic developers: Intel and Brainchip.

Small form factor, magnitudes less power consumption than GPU

On-chip learning for deployment network specific attack detection

Intel Loihi

Brainchip Akida

S04

Dashboards Minimize Operator Fatigue

A robust, multi-faceted, user-friendly cyber analyst dashboard prevents operator fatigue that allows cyber attacks to happen. Large numbers of false alarms cause real threats to be missed, and false alarms fatigue the cyber analyst, further increasing the risk of missed threats.

AI based false alarms are minimized, trained for minimal false positive rate

Possible threats are ranked by importance and confidence

Only the most relevant and likely alarms are actioned upon

Programme record

Where it came from.

A Quantum Ventura, Lockheed Martin, and Penn State Innovation. CyberNeuro-RT (CNRT) has been developed in partnership with Lockheed Martin Co.'s MFC Division and Pennsylvania State University under partial funding from the U.S. Department of Energy.

Partners	Lockheed Martin Co. MFC Division · Pennsylvania State University
Funding	Partial funding from the U.S. Department of Energy
Deployment	CPU, GPU or low-power neuromorphic chip
Neuromorphic	Intel Loihi · Brainchip Akida

Tell us the program
and the problem.

We reply from San Jose, usually within two working days.

Request a demo → Meet the team