An IBM Researcher has solved a mathematical problem that has confounded scientists since the invention of public-key encryption several decades ago.
The breakthrough makes possible the deep and unlimited analysis of encrypted information — data that has been intentionally scrambled — without sacrificing confidentiality.
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.
Using the solution could help strengthen the business model of “cloud computing,” where a computer vendor is entrusted to host the confidential data of others in a ubiquitous Internet presence.
Other potential applications include enabling filters to identify spam, even in encrypted email, or protecting information contained in electronic medical records.
“At IBM, as we aim to help businesses and governments operate in more intelligent ways, we are also pursuing the future of privacy and security,” said Charles Lickel, vice president of Software Research at IBM. “Fully homomorphic encryption is a bit like enabling a layperson to perform flawless neurosurgery while blindfolded, and without later remembering the episode. We believe this breakthrough will enable businesses to make more informed decisions, based on more studied analysis, without compromising privacy.”
Craig Gentry conducted research on privacy homomorphism while he was a summer student at IBM Research and while working on his PhD at Stanford University.
IBM Research is home to the largest team of cryptography researchers outside of the academic and government communities.