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 ...

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 ...

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 ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

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 ...

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 ...

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 ...