IBM Corp. on Thursday released a free toolkit meant to make it practical for developers to implement fully homomorphic encryption, an emerging cryptography scheme with the potential to be safer than current methods and more resistant to quantum computers.

The toolkit is available on iOS and MacOS at launch. A few weeks from now, IBM plans to add support for Linux as well as an Android-friendly version.

Fully homomorphic encryption, or FHE for short, is a cryptographic scheme pioneered in 2009 by noted computer scientist Craig Gentry, who at the time worked at IBM Research. The  security issue it aims to solve is that even encrypted data isn’t encrypted all of the time. Files must be unscrambled whenever an application needs to use them, which creates openings for hackers to swoop in and steal their contents. 

FHE doesn’t have this weak point. The technology allows an application to process data in its encryption form and generate results, which are encrypted as well, that are identical to the results the application would receive if it processed data normally. But while powerful in theory, FHE has been difficult to implement in practice because of the difficulty of implementing it, which is what IBM’s new framework aims to change.

“Developers with basic platform tool familiarity can get up and running by following a few simple instructions rather quickly,” Flavio Bergamaschi, the head of the FHE research group inside IBM Research, wrote in a blog post.  “It was no small feat to synthesize 11 years of top-notch cryptography research into a streamlined developer experience.”

The toolkit includes an example implementation to help developers learn the ropes and IBM has released separate resources, including a Slack channel, to further lower the learning curve. It will also be offering technical training to enterprise customers. 

In its current stage of development, FHE is too computationally intensive to be useful for all encryption use cases, but it has promising applications for companies such as banks that work with sensitive data. Customer analytics is one of the use case that could benefit. IBM said it has worked with Banco Bradesco S.A, one of Brazil’s largest banks, on a project wherein the firm’s analysts successfully ran queries against an encrypted customer dataset without having to expose the raw records.

Data sharing between organizations is another use case IBM is eyeing. Healthcare companies, as an example, share medical datasets with one another for research purposes but must avoid revealing the identities of the patients to which the records belong. FHE makes it possible to encrypt parts of a dataset while still permitting less sensitive portions to analyzed.

In the long term, FHE could emerge as particularly valuable because it’s believed to be resistant to quantum encryption cracking. Cryptography secures files by making access to the data contingent on a computer solving a complex mathematical problem. The types of problems used by the most popular encryption schemes today could theoretically be solved by a large enough quantum computer, but FHE relies on a different approach based on constructs known as lattices that researchers estimate will be harder to crack.

There are multiple ways FHE can fit into IBM’s strategy in the future. The company could potentially use it to enhance the features of its cryptography products, as well as harness FHE in some of the projects taken on by its cybersecurity consulting business.

Image: IBM