Machine Vision Pilot (MVP) and Microelectronic Authenticity and Security, Evaluation and Research (MASER)

Principal Investigator: Dr. Michael H. Azarian1
Co-Principal Investigator: Dr. Diganta Das1
Principal Investigator: Prof. Patricia E. Campbell2
DMEA Project Engineer: Jeff Carlile, DMEA3

1Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD, USA
2University of Maryland Carey School of Law at the University of Maryland, Baltimore
3Defense Microelectronics Activity (DMEA)

Project Team:

Defense Microelectronics Activity:
Mr. Jeff Carlile, Mr. Michael Sutherland, Mr. Daric Matthew Guimary, Mr. Phil Comer, Mr. Aaron Schaal, Mr. Kevin Hartmann, Mr. Isaac Fields, Mr. Jamesson Kaupanger

Contributors from University of Maryland College Park:
Mr. Devon Richman, Mr. Jesse Hearn, Mr. Peter Kuffel, Mr. John Freal

Contributors from University of Maryland Carey School of Law:
Mr. George (Kenny) Eichelman, Ms. Kirsten Gallo, Mr. Jared MacKenzie, Mr. Troy Walker

Contributors from SMT Corp:
Mr. Tom Sharpe

Executive Summary:

Section 843 of the 2018 National Defense Authorization Act (NDAA) (known as the “John S. McCain National Defense Authorization Act for Fiscal Year 2019”) authorized funding to establish a “Pilot program to test machine-vision technologies to determine the authenticity and security of microelectronic parts in weapon systems.” In order to accomplish this, the act provided that the Undersecretary of Defense for Research and Engineering work in coordination with the Defense Microelectronics Activity to establish the program, which was to be completed no later than December 30, 2020. The Defense Microelectronics Activity (DMEA) established two contracts to carry out the tasks identified in the 2018 NDAA §843. DMEA contracted the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland at College Park to execute the pilot program under both contracts.

The stated purpose of the pilot program was to test the feasibility and reliability of using machine- vision technologies to determine the authenticity and security of microelectronic parts in weapon systems. The primary focus of the project is the prevention and detection of counterfeit microelectronics from entering the supply chain. For the purposes of this effort, the term “Machine Vision” was defined as systems which detect signals within the electromagnetic (EM) spectrum, not only the frequencies visible to the human eye. Systems which rely on image comparison are referred to as “Image Analysis” within this effort. The program included an evaluation of two types of Machine Vision: Image Analysis, and Side Channel, and included conventional standards-based testing methods as applied to counterfeit microelectronics detection. It provided quantitative data on their effectiveness, as well as recommendations for suggested improvements to counterfeit detection methods. It included Technology Readiness Level (TRL) assessments to identify promising counterfeit detection methods that can be implemented successfully and quickly.

A policy analysis was conducted to identify potential impediments to effective implementation of existing laws and regulations, and to indicate steps that can enhance the effective application of such rules, regulations, or processes to mitigate counterfeit microelectronics proliferation throughout the DoD. It also identified the policy considerations and recommended actions necessary for Machine Vision to be implemented in counterfeit detection and authentication of electronic parts...

The Executive Summary continues in the main report.

This report is available online here.

For more information about this report and related research, please contact Dr. Michael H. Azarian and Dr. Diganta Das.

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