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 ...

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 ...

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 ...

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 problem with encrypted data is that you must decrypt it in order to work with it. By doing so, it’s vulnerable to the very things you were trying to protect it from by encrypting it. There is a ...

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 ...

In the Tech sector there are few areas of the market that are as critical and burgeoning with opportunity as security. Simply put, the more connected we become and the more data we amass, the more we ...

How FHE has evolved from a theoretical concept to a practical technology that’s ready for real-world applications. The unique benefits and challenges of implementing FHE, including why specialized ...

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 ...

Craig Gentry is creating an encryption system that could solve the problem keeping many organizations from using cloud computing to analyze and mine data: it’s too much of a security risk to give a ...