The Problem This Solution Solves
The U.S. defense industrial base is a large, complex, and geographically-dispersed network of interconnected stakeholders, suppliers, and activities. Threats to this industrial base, particularly in regards to critical technologies, are significant and actively evolving. For example, reliance on foreign-owned or -controlled hardware, software, or services introduces opportunities for exploitation of a product’s integrity, trustworthiness, and authenticity. Past incidents with manufacturers and their supply chains highlight the difficulties of ensuring availability or identifying the source, authenticity, quality, and security of critical assets used by the DoD.
The Solution
Lilt relies on machine learning to process and translate large quantities of supply chain data to automate the identification of supply chain risks. Lilt’s solution then aggregates identified threats into analytical reports provided to DoD analysts in an effort to enhance their understanding of adversarial activities. Testing revealed that Lilt’s modern machine learning translation techniques outperform current translation methods by reducing time to threat detection by 75%.