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IBM releases open-source toolkits implementing FHE to process data while encrypted

IBM has released open-source toolkits implementing fully homomorphic encryption (FHE) that allow researchers to process data while it’s still encrypted. IBM has released open-source toolkits implementing fully homomorphic encryption (FHE), which allows researchers to process encrypted data without having access to the actual data. The toolkits released by IBM are already available for macOS and […]

Trusted Platform Module 2.0 flaws

IBM has released open-source toolkits implementing fully homomorphic encryption (FHE) that allow researchers to process data while it’s still encrypted.

IBM has released open-source toolkits implementing fully homomorphic encryption (FHE), which allows researchers to process encrypted data without having access to the actual data.

The toolkits released by IBM are already available for macOS and iOS, the IT company plan to release also Android and Linux versions.

The FHE toolkits are been released on GitHub for macOS and iOS.

IBM invented FHE in 2009, but only recently it is becoming practical thanks to algorithmic progresses. 

“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,” states IBM.

FHE is the killer application for major industries, including the financial and healthcare sectors. FHE could allow associating data to be shared without exposing it while processing the information.

FHE could be implemented to enact “privacy preserving search” that allows users to search against a cloud service without revealing their queries’ data to the cloud provider. 

IBM also described another use case in which developers of machine learning systems could train their model using encrypted data provided by others analyzing the same type of problem, but without having access to the actual data.

“Your model would benefit from this superset of encrypted data without individual parties making their data public.” reads a blog post published by IBM.

“For example, what if all the health care providers on the planet could pool fully encrypted patient records to allow analytics on patient data without divulging anything about the individuals involved. Think of the progress that could be made with regards to treating certain kinds of diseases!”

Every scenario where information-sharing collides with the paradox of ‘need-to-know’ vs. ‘need to share’ would benefit from FHE.

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Pierluigi Paganini

(SecurityAffairs – FHE, cybersecurity)

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