An IBM researcher has solved a complicated mathematical problem that has confounded scientists since the invention of public-key encryption several decades ago. The breakthrough, called "privacy homomorphism," or "fully homomorphic encryption," makes possible the deep and unlimited analysis of encrypted information -- data that has been intentionally scrambled -- without sacrificing confidentiality.

Craig Gentry uses a mathematical object called an "ideal lattice" to let people fully interact with encrypted data in ways previously thought impossible. With the breakthrough, computer vendors storing the confidential, electronic data of others will be able to fully analyze data on their clients' behalf without expensive interaction with the client, and without seeing any of the private data. With Gentry's technique, the analysis of encrypted information can yield the same detailed results as if the original data was fully visible to all.

Potential applications include enabling filters to identify spam, even in encrypted email, or protecting information contained in electronic medical records. The breakthrough might also one day enable computer users to retrieve information from a search engine with more confidentiality.

"Fully homomorphic encryption is a bit like enabling a layperson to perform flawless neurosurgery while blindfolded, and without later remembering the episode," says IBM Research's Charles Lickel. "We believe this breakthrough will enable businesses to make more informed decisions, based on more studied analysis, without compromising privacy. We also think that the lattice approach holds potential for helping to solve additional cryptography challenges in the future."

Ron Rivest and Leonard Adleman, along with Michael Dertouzos, introduced and struggled with the notion of fully homomorphic encryption approximately 30 years ago. Although advances through the years offered partial solutions to this problem, a full solution that achieves all the desired properties of homomorphic encryption did not exist until now.