Fully homomorphic encryption using a C++ transpiler

On the upside, the benefits of big data are revolutionary and immensely helpful to the user, everything from recommender systems to fraud prevention. Only if there was a way to share data without violating the user’s privacy? Well, good news. There is, and it’s called homomorphic encryption.

Homomorphic encryption is a way to perform mathematical operations on encrypted data without decrypting them. It was first theorized in the late seventies. Homomorphic encryption refers to partially homomorphic encryption(PHE) and fully homomorphic encryption(FHE) in general. The difference between FHE and its lesser counterpart is that FHE supports addition, subtraction, multiplication, and division, while the other doesn’t.

Imagine you work for a bank, and you want to understand what customers spend their money on, so you can offer your customers better bargains. To achieve this goal, you partner with an organization to perform witchcraft on the data to understand customer spending patterns. As unadulterated as your intentions are, how would the customers feel about it? With FHE you can share the customer data in an encrypted form so that the organization performing the witchcraft only see encrypted random data and not the actual customer information. Let’s see how we can put this to practice.

The good folks at Google recently open-sourced a general-purpose FHE transpiler. The example below performs a simple sum of two numbers. Notice the raw values and the encrypted values.h