More efficient security for cloud-based machine learning: Novel combination of two encryption techniques protects private data, while keeping neural networks running quickly

Outsourcing machine learning is a rising trend in industry. Major tech firms have launched cloud platforms that conduct computation-heavy tasks, such as, say, running data through a convolutional neural network (CNN) for image classification. Resource-strapped small businesses and other users can upload data to those services for a fee and get back results in several hours. But what if there are leaks of private data? In recent years, researchers have explored various secure-computation techniques to protect such sensitive data.