A new study shows public views on data privacy vary according to how the data are used, who benefits, and other conditions.

The approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.

A first history of the document security technology, co-authored by MIT Libraries’ Jana Dambrogio, provides new tools for interdisciplinary research.

New “Oreo” method from MIT CSAIL researchers removes footprints that reveal where code is stored before a hacker can see them.

The consortium will bring researchers and industry together to focus on impact.

The technique leverages quantum properties of light to guarantee security while preserving the accuracy of a deep-learning model.

Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.

Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.

The ambient light sensors responsible for smart devices’ brightness adjustments can capture images of touch interactions like swiping and tapping for hackers.

Speranza system brings hope to users that the package they download is functional software, not malware.