What do you do when you need to perform computations on large data sets while preserving their confidentiality? In other words, you would like to gather analytics, for example, on user data, without ...

AI and privacy needn’t be mutually exclusive. After a decade in the labs, homomorphic encryption (HE) is emerging as a top way to help protect data privacy in machine learning (ML) and cloud computing ...

Yesterday, Ars spoke with IBM Senior Research Scientist Flavio Bergamaschi about the company’s recent successful field trials of Fully Homomorphic Encryption. We suspect many of you will have the same ...

Secure cloud data processing has become a critical issue in recent times and while general network security techniques such as Virtual Private Networks could be used for securing the end-to-end ...

Organizations are starting to take an interest in homomorphic encryption, which allows computation to be performed directly on encrypted data without requiring access to a secret key. While the ...

Modern cryptography is embedded in countless digital systems and components. It's an essential tool for keeping data secure and private. Yet one of the biggest limitations with cryptography, including ...

The history of homomorphic encryption stretches back to the late 1970s. Just a year after the RSA public-key scheme was developed, Ron Rivest, Len Adleman, and ...

Apple recently open sourced its homomorphic encryption library for Swift, enabling developers who use the Apple programming language to implement the privacy-preserving technology. Homomorphic ...

Forbes contributors publish independent expert analyses and insights. Dave Altavilla is a Tech Analyst covering chips, compute and AI. In the Tech sector there are few areas of the market that are as ...