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 ...

Regardless of the strength of data’s encryption, more and more potential vulnerabilities surface in data security as more people are granted access to sensitive information. However, a relatively new ...

The partnership aims to improve performance and accuracy of FHE to make it practical for business and government to better protect confidential data in the cloud. Intel has partnered with Microsoft as ...

Data has been called the new oil—the 21st century's most valuable commodity. Due to this value, we have entered an era where data breaches are not just a threat but a frequent headline. Regardless, ...

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 ...

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 ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. The panelists discuss the dramatic escalation ...

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 ...