The Department of Homeland Security’s Science and Technology Directorate is soliciting technology proposals designed to generate synthetic data that replicates authentic data patterns while maintaining the privacy and security of information.
DHS S&T said Friday that synthetic data generator technologies will enable the department to train machine learning models and artificial intelligence applications when real-world data is unavailable or when using real data would pose privacy and security risks.
The topic call is being issued under the Silicon Valley Innovation Program other transaction solicitation and is seeking technologies that could support structured and unstructured data types, artificially generate synthetic data, replicate data sets with desired statistical attributes, verify data fidelity and remove bias in synthetic data.
“The ability to generate synthetic data at scale is necessary to protect and preserve data privacy, as well as safeguard civil rights and liberties,” said Melissa Oh, managing director of S&T’s SVIP initiative.
Applications to the solicitation are due April 10.
