Protopia AI is at RSAC. Meet our team of experts in AI Data Privacy and Security.
Government and defense agencies face unique challenges when it comes to AI data access and data protection. Enable timely access to insights using the best AI algorithms without compromising sensitive information.
Stained Glass Transform can be used to analyze video and image data for security purposes while protecting the identities of individuals in the images.
Agencies look to share intelligence insights without exposing underlying data to each other in unprotected/human-understandable representations.
When training or using ML models for Detection and Response (MLDR), neither the training data nor the data used for predictions need to be exposed. Maximizing protection for your network data should be essential to your MLDR cybersecurity strategy.
Protopia AI partnered with NetApp and implemented Stained Glass Transform™ to demonstrate the breakthrough capability of being able to perform a task like real-time face recognition of VIPs without exposing unprotected images. This capability was showcased at the annual Trident Warrior exercise.
The solution transformed subjects’ faces into Randomized Re‑Representations that were only readable by the facial recognition model with near‑perfect accuracy to identify VIPs. The use case showcased Stained Glass’ ability to protect real-time AI deployment successfully.
Private inference architecture, powered by Protopia AI’s Stained Glass, directly strengthens multiple ARMOR domains.
The application-layer breach has known fixes, and McKinsey has applied them. The inference pipeline is the second layer, and it is the one Mythos should reframe.
AI Factory ROI depends on using high-value data at full fidelity and running compute at full capacity. Privacy constraints force operators to choose one or the other. HPE and Protopia AI have validated a blueprint that eliminates that tradeoff through private multi-tenant inference.