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 ...

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 ...

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 ...

Privacy is a core concern in crypto. Once you know a crypto wallet address corresponds to a certain individual, you can track all the transactions that individual has ...

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 ...

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 ...