IBM crypto snoops data without looking

An IBM researcher has solved a tricky mathematical problem that makes it possible to analyse encrypted data without compromising privacy.

Craig Gentry used a mathematical object called an ideal lattice to develop a system called fully homomorphic encryption (apparently you might also know it as 'privacy homomorphism').

Basically, the system allows IBM to fully interact with encrypted data in ways that were previously thought impossible.

Securing the cloud

With the breakthrough, companies storing confidential, electronic data will be able to analyse data on their clients' behalf without expensive interaction, and without actually seeing any of the private data.

For instance, it could allow cloud computing companies to process months of confidential sales data, without exposing the original information.

Other potential applications include enabling filters to identify spam, even in encrypted email, or protecting information contained in electronic medical records. Eventually, homomorphic encryption could let users retrieve information from a search engine with complete confidentiality.

Get that cat out of here!

Charles Lickel, vice president of Software Research at IBM said: "Fully homomorphic encryption is a bit like enabling a layperson to perform flawless neurosurgery while blindfolded, and without later remembering the episode."

"We also think that the lattice approach holds potential for helping to solve additional cryptography challenges in the future," he added.

Fully homomorphic encryption was first suggested 30 years ago but it's only now that a complete mathematical solution has been developed.