Distributed ledger-based hybrid quantum machine learning ransomware security

Abstract

Disclosed are various approaches for distributed ledger-based hybrid quantum ransomware security. In some examples, ransomware detection can be performed on a file. The ransomware detection can include converting the file into image data comprising an image data format, processing the image data using a convolutional neural network to generate a feature map, and providing the feature map to a variational quantum circuit machine learning engine. An action can be performed based at least in part on an output from the variational quantum circuit machine learning engine.