Decision Tree

Using data from the UCI Machine Learning Repository, we constructed a decision tree model to identify benign and malignant tumors. After creating the decision tree model, it was processed by patented RHYPT technology to create an obfuscated and encrypted function. Both the data and function values are encrypted and secured, as shown in this interactive demo.

Decision Tree Demo Visualization

Convolutional Neural Network - MNIST

Using the MNIST Handwritten Digist Database, we constructed a simple convolutional neural network to identify written numbers. After creating the network, it was processed by patented RHYPT technology to create an obfuscated and encrypted function. Both the data and function values are encrypted and secured, as shown in this visual demo.

Convolutional Neural Network Demo Visualization