Future-oriented cyber defense is the next-gen strategy of national security and enterprise security. Similar and complementary to EINSTEIN, DC2.5, the flagship solution of DeepCyber, PAMDs (predict | attenuate | monitor | detect) cyber attacks to enterprise/IoT networks and data centers. According to Bloomberg and Yahoo news, the EINSTEIN program is funded about $350 million each year.
DC2.5 is a cutting-edge (AI algos being patented), powerful (cyber sensors) and affordable COTS cyber defense SaaS system powered by our research and development breakthroughs in automated prediction and deep learning AI algorithms. DC2.5, PNN and MCPS are being patented by USPTO.
DC2.5, a cyber analytics SaaS cloud, is engineered on a hybrid IaaS/PaaS cloud with multiple cloud service providers inclusive of Amazon Web Services (public cloud) and DeepCyber's Open-stack powered private cloud - MCPS (Mobile Cloud on Pangu Servers) designed by DARPA specs. DC2.5 is developed in the D language on an API/SOA architecture that seamlessly integrates more than 5 standard programming/scripting languages.
Extending PNN, the first visual AI solution for asset trendspotting, DC2.5 is the first visual AI machine for predicting cyber attacks with high back-test accuracy. DC2.5 enables automated modeling and prediction for cyber attacks from large data sets
Modeling complex non-linear datasets is hard: it takes a PhD student 3-5 years to conceptualize, develop and optimize a quantitative model. DC2.5 automates the modeling within days and runs the model for prediction within minutes.
DC2.5 AI machine runs on an MCPS cloud platform that is powerful, portable and interoperable. MCPS offers an end to end Big Data cloud capability of massively parallel processing (MPP) and linear scaling. Mobile Cloud on Pangu Servers (MCPS) = mini(AWS + DropBox + Cloudera + SAS) + Portability + Interoperability.
DC2.5's AI cloud machine is designed by DeepCyber, a private U.S. company specializing in cyber security, automated modeling and prediction, Cloud and Big Data solutions.
Email: firstname.lastname@example.org. Corporate address: 2711 Centerville Road, Suite 400, Wilmington, Delaware 19808, USA
A predictive AI chart for the UCI (U.S. CyberRisk Index) production data is available upon request. For collaboration, you may want to request a proof of concept with your cyber dataset or REST API endpoint for DC's AI cloud engine. This shall produce AI predictive charts on the cyber metrics (e.g., CVSS) of your choice. DC2.5's AI cloud machine automates modeling to predict cyber attacks.