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DATUM: Determining Authenticity and Trustworthiness of Microelectronics Parts

Award Information
Agency: Department of Defense
Branch: Defense Microelectronics Activity
Contract: HQ072720P0011
Agency Tracking Number: 19-9K2
Amount: $167,500.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: DMEA192-002
Solicitation Number: 19.2
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2019-11-21
Award End Date (Contract End Date): 2020-09-10
Small Business Information
15400 Calhoun Drive Suite 190
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Shahin Lotfabadi
 Senior Engineer
 (301) 294-5279
Business Contact
 Mark James
Phone: (301) 294-5200
Research Institution

The aging supply chain management is the available long term protection against IC counterfeiting. For better protection, there is an urgent need for an advanced counterfeit detection system. The industry has made progress in cataloging the features in counterfeit parts and the physical tools to detect them. However, the methods still largely depend on human skills which are time consuming and often not repeatable. Moreover, although there are available techniques to detect changes against a golden sample, there is a need to determine if the changes exclude those made due to the authentic product changes. IAI proposes to develop a cost effective software solution to detect counterfeit parts using machine learning and machine vision algorithms that go beyond traditional approaches. The proposed detection method will analyze images not only from traditional radiography, tomography acoustic images, but also spectroscopy images (e.g., X-ray fluorescence spectrometry, and Fourier transform infrared spectroscopy). The analysis will be tested against the defects catalogue in industry, particularly SAE 6171. The proposed analysis will classify differences between original design and device under test, to guaranty all changes are authorized. The analysis technique will also be adopted to the cases where comparative golden samples are not available.

* Information listed above is at the time of submission. *

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