Fully Homomorphic Encryption

How to achieve data privacy by design

Research objective

For decades, we have benefitted from modern cryptography to protect our sensitive data during transmission and in storage. However, we have never been able to keep the data protected whilst it is being processed.

In the past, cryptographic schemes that allowed processing on encrypted data were limited to partial homomorphic schemes that could support only one fundamental operation, namely either addition or multiplication but not both. Then in 2009 IBM pioneered Fully Homomorphic Encryption, which supports both fundamental operations, thus enabling the processing of data without giving access to it, however at this time it was too slow for practical use.

In recent years, thanks to algorithmic advancements, Fully Homomorphic Encryption has reached an inflection point where its performance is becoming practical. This has revolutionized security and data privacy and how we outsource computation to untrusted clouds.

Fully Homomorphic Encryption promises to disrupt major industries such as finance, healthcare, infrastructure and government by unlocking the value of data previously unreachable due to the paradox of need-to-know versus need-to-share between data custodians and data users/exploiters. For example, Fully Homomorphic Encryption makes it possible to share financial data or patient healthcare records for analytics or cross-industry collaboration without giving access to the private data.