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 ...

Fully Homomorphic Encryption (FHE) for years has been a promising approach to protecting data while it’s being computed on, but making it fast enough and easy enough to use has been a challenge. The ...

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 ...

Data theft and data loss is an endemic problem on the internet. According to the firm Risk Based Security (via TechRepublic), 2020 alone saw 3,932 publicly disclosed breaches with 37 billion records ...

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 ...

The world has gotten a lot more serious about privacy and data protection, but in many cases business models that rely on personalization of one kind or another have struggled to keep up. Today, a ...

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 ...