CyberNeuro-RT

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

Hero image for Quantum
A Quantum Ventura, Lockheed Martin, and Penn State Innovation
Quantum Ventura’s CyberNeuro-RT (CNRT) technology offering 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.
Cutting-Edge Unsupervised ML

Scalable Unsupervised Outlier Detection (SUOD)

  • Large-scale heterogeneous outlier detection
  • 6 ML Algo EnsembleModel Approximation for Complex Models
  • Execution Efficiency Improvement for Task Load Balancing in Distributed System
  • Variational Autoencoder (VAE)

Variational Autoencoder (VAE)

  • Encoder-Decoder Architecture
  • Variational => Highly Regularized Encoder
  • ETrained to Minimize Reconstruction Error of initial input and reconstructed output
  • Variational Autoencoder (VAE)
75x Dataset Growth in Under 2 Months
  1. Existing Dataset Ingestion: Proprietary system enables ingestion of any existing network capture dataset with flexible support for any labelling system
  2. From-the-wild Zero Day Sampling: System enables capturing and simulation of novel threats for additional data sampling
  3. Data Generation via Simulation: ThreatATI database and proprietary ingestion system enable sampling and augmentation for cataloged threats from proprietary and public threat databases
Proprietary Pipeline Adapts to Any Dataset
This is an illustration showing that the Proprietary Pipeline adapts to any dataset
Follow Threats Home with Dark Web Tracking
List of threats
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

An image showing Intel Loihi
Intel Loihi
A Brainchip Akida
Brainchip Akida
Dashboards Minimizes Operator Fatigue

Robust, multi-faceted, user-friendly Cyber Analyst dashboard Operator fatigue allows cyber attacks to happen

  • Large numbers of false alarms cause real threats to be missed
  • False alarms fatigue the cyber analyst further increasing risk of missed threats

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The Cyber Neuro-RT dashboard is designed to minimize all sources of analyst fatigue while presenting timely and meaningful data insights

  • Al based false alarms are minimized (trained for minimal false positive rate)n for cataloged threats from proprietary and public threat databases
  • Possible threats are ranked by importance and confidence
  • Only the most relevant and likely alarms are actioned upon