News

Under the Collaboration, Duality Will Develop a Privacy-Preserving Research Framework Based on the Palisade Open-Source Homomorphic Encryption (HE) Library to Enable Academic Institutions and Public Agencies to Share Data and Evaluate the Effects of Grant-Making to Students

Duality Technologies announced that it has contracted with the Defense Advanced Research Projects Agency (DARPA) to develop a privacy-preserving Machine Learning (ML) capability that can train models on encrypted data from multiple sources.

Duality Technologies, a leading provider of Privacy-Enhancing Technologies (PETs) enabling privacy-preserving data sharing and collaboration, announced the formation of its advisory board

New privacy-enhancing techniques like homomorphic encryption, federated learning, and differential privacy can help us use data for the greater good without sacrificing individual data rights.

A startup maker of data-encryption technology believes it has the answer to the security problem that has hampered researchers looking to perform massive genome-wide association studies with datasets from disparate sources, even when the records are located in different countries.

Financial institutions are investing substantial resources in combating money laundering and other forms of financial crime.

Privacy-Enhancing Technologies (PETs) can strike a balance between public health and privacy by enabling privacy-enhanced information sharing without exposing individuals’ private data.

Researchers affiliated with Duality Technologies have published a study on applying a privacy-preserving AI technique — homomorphic encryption (HE) — to large-scale, genome-wide association studies (GWAS) on genetic and phenotype data.

Computer scientist Shafi Goldwasser’s startup Duality Technologies develops a technology that allows authorities to monitor the spread of coronavirus and gain meaningful insights from encrypted data, without compromising the privacy of citizens

As apps tracing Covid-19 spring up, there are fears for the safety of our private data. But Shafi Goldwasser may have the solution.