Google announces open-sourcing a first-of-its-kind, general-purpose transpiler for Fully Homomorphic Encryption (FHE), which will enable developers to compute on encrypted data without being able to access any personally identifiable information.
What is Homomorphic Encryption?
Homomorphic encryption is a form of encryption that permits users to perform computations on its encrypted data without first decrypting it. These resulting computations are left in an encrypted form which, when decrypted, result in an identical output to that produced had the operations been performed on the unencrypted data.
Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted.
What is Fully Homomorphic Encryption?
Fully Homomorphic Encryption (FHE) is an emerging data processing paradigm that allows developers to perform transformations on encrypted data. FHE can change the way computations are performed by preserving privacy end-to-end, thereby giving users even greater confidence that their information will remain private and secure.
With FHE, encrypted data can travel across the Internet to a server, where it can be processed without being decrypted. Google’s transpiler will enable developers to write code for any type of basic computation such as simple string processing or math, and run it on encrypted data. The transpiler will transform that code into a version that can run on encrypted data. This then allows developers to create new programming applications that don’t need unencrypted data.
For example, imagine you’re building an application for people with diabetes. This app might collect sensitive information from its users, and you need a way to keep this data private and protected while also sharing it with medical experts to learn valuable insights that could lead to important medical advancements.
With Google’s transpiler for FHE, you can encrypt the data you collect and share it with medical experts who, in turn, can analyze the data without decrypting it – providing helpful information to the medical community, all while ensuring that no one can access the data’s underlying information.
Making more products private by design
Our principle to make our products private by design drives us to build ground-breaking computing technologies that enable personalized experiences while protecting your private information. Privacy-preserving technologies are on the cutting-edge of Google’s innovations, and they have already shown great potential to help shape a more private internet.
To process your data, homomorphic encryption does not require that you decrypt your data first. Through homomorphic encryption, ciphertexts can be processed in such a way that the encrypted output matches the results that would have been produced by initially decrypting the input data, processing them, and finally encrypting them. Google says FHE can be used to train machine learning models using sensitive data.