TRIO AI/ML SYSTEM FOR CYBER SECURITY

Metronome proposes Trio SBIR Phase II with the goal to build, test and demonstrate a large-scale and highly horizontally-scalable Artificial-Intelligence-(AI)-based (Machine Learning, ML – Neural Network, NN) anomaly detection system  with distributed networking, Graphical User Interface (GUI) control console and visualization capabilities.  These AI-based anomaly detection capabilities are to be built from Phase-I achievements in successful developments of key Trio elements (Feature Engineering pipeline, Trio Intelligent Agent (IA) Type 1 (Machine Learning, ML), IA Type 2 (Neural Network, NN) and IA Type 3 (ML)) plus to be integrated with a Zero-Trust security framework to complete Trio product offerings for cybersecurity. The main technical objectives to achieve the above-stated goal consist of the following: 1) Implement additional capabilities (including Zero Trust Security framework) and features for large-scale operations by expanding Phase-I implementations for horizontal scalability, big-data streaming/ingestion capability, big-data data storage, processing and visualization capabilities 2) Productionize all software designs from end to end by testing for algorithm robustness. 3) Productize into deployment/commercialization packages for various configurations in deployments. Metronome also proposes to employ Zscaler, Inc. as our subcontractor/R&D-partner in Phase II. Zscaler will integrate its FedRAMP-certified Zero-Trust security framework, known as Zscaler Private Access (ZPA), which has been deployed worldwide, with Metronome’s Trio, ensuring a complete cybersecurity product portfolio, assuring the production-level quality of Trio and enhancing the Technical Readiness Level (TRL).