WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announces the winners of the Nail to Nail Fingerprint—“N2N”—Challenge, a competition to develop and enhance automated methods to capture accurate nail to nail fingerprints comparable or better than the existing standards for accuracy, speed, and invisible, “latent,” capture accuracy. The N2N challenge launched in February 2017 and sought challengers from around the world to develop automated N2N capture technology capable of biometric recognition that is as good as, or better than, existing standard human operator assisted methods.

Issuance of Updated Intelligence Community Directive 107 on Civil Liberties, Privacy, and Transparency

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced today the launch of the Virtuous User Environment—“VirtUE”—program to improve the way users interact with their daily computers to protect an organization from cloud-based security vulnerabilities. “The commercial cloud and the numerous innovative technologies that it is spawning offers computer security professionals the ability to recreate a user environment that is fundamentally more secure than current workstation and virtual desktop offerings while still being accessible and affordable,” says IARPA program manager Kerry Long.

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announces today the UG2 Prize Challenge for unmanned aerial vehicles, gliders, and ground data entries. The challenge aims to advance the analysis of images collected by small UAVs by improving image restoration and algorithm performance.

WASHINGTON – The Intelligence Advanced Research Projects Activity, within the Office of the Director of National Intelligence, announced the winners of the functional Map of the World—“fMoW”—Challenge, a competition that called for contestants to develop automated techniques to accurately categorize points of interest from satellite imagery. There were 69 participants, “solvers,” who competed for a total $100,000 prize purse; the top three developers Open Sourced their solutions that can be used to further improve geospatial computer vision efforts. First through fifth place winners were comprised of both industry and academia.