SBIR/STTR Research Award
Applications of Machine Learning and Machine Vision to Determine the Authenticity and Security of Microelectronics Parts in Weapons Systems
Award amount
$167,438Program and phase
SBIR · Phase IAward year
2020Award details
- Awarding agency
- Department of Defense
- Branch
- Defense Microelectronics Activity
- Recipient company
- ALITHEON INC
- Proposal award date
- 2019-11-26
- Contract end date
- 2020-04-10
- UEI
- MMJFE4B5MQP1
- Solicitation number
- 19.2
- Topic code
- DMEA192-002
Research abstract
Alitheon proposes a study of the feasibility of the use of its FeaturePrintTM technology to ensure the authenticity and security of microelectronics parts used in weapons systems.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- FeaturePrint: Digital Fingerprinting for Secure Multi-Die System Supply Chains
- Digital Fingerprinting to Overcome Distance and Complexity for Supply Chain Security
- FeaturePrint: Computer Vision for Pebble Bed Reactors' Material, Control, and Accounting
- FeaturePrint: Irrefutable Nuclear Supply Chain Security
- Alitheon Nuclear Pitch Day Submission
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Rapid, Portable, Surface Texture Based Component Classifier (RAPSTEC) System
- Machine Learning Applied to Counterfeit Detection
- Rapid, Portable, Surface Texture Based Component Classifier (RAPSTEC) System
- DATUM: Determining Authenticity and Trustworthiness of Microelectronics Parts
- Rapid, Portable, Surface Texture Based Component Classifier (RAPSTEC) System
Research funding history
6 SBIR/STTR records share this UEI (2020–2025). Reported award amounts total $3,411,666. Reported amounts are not federal obligations.
Phases: Phase I, Phase II – Direct to Phase II
Agencies: Department of Defense, Department of Energy