Mobile Vehicle Forensics

U.S. Department of Defense – Navy (SBIR)

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Funder
U.S. Department of Defense – Navy (SBIR)
Award amount
Not specified
Deadline
January 6, 2027
Eligible countries
United States
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Summary

SBIR topic DON27BZ02-NV006 (U.S. Department of Defense – Navy), Phase I and II. Open to U.S. small businesses. Opens: December 2, 2026. Closes: January 6, 2027. Operational Need & Gap: During tactical site exploitation (TSE), Marine Corps and Joint operators require immediate, field-deployable hardware and software to recognize, preserve, and collect materials of forensic value. While multi-purpose forensic kits exist to process traditional materials, a critical intelligence gap remains regarding vehicle-derived data. Modern vehicles function as mobile data hubs featuring advanced navigation, localized track logs, and cached external device connections. Exploiting this telematics and informatics data is vital for generating actionable intelligence, mapping networks, and establishing identity dominance. The Problem (Technological Fragmentation): The primary barrier to tactical vehicle exploitation is severe technological fragmentation. Current vehicle forensic solutions are often designed for controlled laboratory environments. Because In-Vehicle Infotainment (IVI) systems and Electronic Control Units (ECUs) rely on proprietary software architectures and inconsistent file structures, existing tools are often restricted to narrow manufacturer subsets. Consequently, field operators may be forced to perform invasive, time-consuming physical disassembly of the vehicle dashboard—a method that is untenable in many field environments. Scope of Effort: This SBIR topic seeks innovative proposals to develop a low-SWaP (Size, Weight, and Power), ruggedized, all-in-one device that automates the forensic exploitation of vehicle data systems. The system must interface via standard external access points (e.g., On-Board Diagnostic [OBD-II] ports or Universal Serial Bus [USB]); automatically profile the vehicle’s make, model, year, and digital architecture; and execute an automated script to extract and structure data. Crucially, these features must be achieved through a…

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