Enabling public but secure deep learning

The era of considering business transformation digitally is over. Today, the mandate is to transform - and to transform quicker and better than others in the league. This article will spotlight the concept of keeping the data secure and private whilst the data also needs to remain public for deep learning. When the data is encrypted using traditional techniques, it becomes impossible to do any meaningful computation on it in its encrypted form. For a meaningful computation to happen, the data must be decrypted and again encrypted.