Special Notice NAICS 518210

INL Innovation Spotlight Innovative Data Concealment for Secure AI Research: The DIOD Methodology The DIOD methodology offers a groundbreaking approach to share critical data for AI research, ensuring confidentiality while maintaining data utility. Overview: In the era of big data, it is crucial to share information across platforms and organizations for innovation, especially in fields like AI research. However, the risk of sensitive data being reverse-engineered or compromised poses a significant challenge. Traditional data anonymization techniques often fall short, either by limiting data utility or failing to fully protect against data breaches. The DIOD (Deceptive Infusion of Data) methodology emerges as a solution, particularly relevant for industries where data sharing is essential yet risky, such as defense, healthcare, and energy. Its market potential is vast, considering the increasing reliance on AI for materials discovery, energy optimization, and security. Description: The DIOD methodology is an innovative approach to data sharing that successfully hides the identity of the system from which data originates, while still maintaining the functional dependencies required ...

Notice ID: aaac36bb101f45ea8014d378f1e9bd69 · View on SAM.gov ↗