cybersecurity
cybersecurity

New security protocol shields data from attackers during cloud-based computation

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

3 Questions: How to prove humanity online

AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?

Melissa Choi named director of MIT Lincoln Laboratory

With decades of experience working across the laboratory’s R&D areas, Choi brings a focus on collaboration, technical excellence, and unity.

Eric Evans receives Department of Defense Medal for Distinguished Public Service

The award recognizes his contributions as director of MIT Lincoln Laboratory and as vice chair and chair of the Defense Science Board.

HPI-MIT design research collaboration creates powerful teams

Together, the Hasso Plattner Institute and MIT are working toward novel solutions to the world’s problems as part of the Designing for Sustainability research program.

This tiny chip can safeguard user data while enabling efficient computing on a smartphone

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

Eric Evans to step down as director of MIT Lincoln Laboratory

During 18 years of leadership, Evans established new R&D mission areas, strengthened ties to the MIT community, and increased inclusion and education efforts.

Accelerating AI tasks while preserving data security

The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.

Four Lincoln Laboratory technologies win five 2023 R&D 100 awards

Inventions in medical imaging, aircrew scheduling, data security, and quantum networking are named among the year’s most innovative new products.

A new way to look at data privacy

Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.