IC Counterfeit Detection Using Physical Inspection Methods Group 173 Project Members: Kevin King (Electrical Engineering) David M. Orosz (Electrical Engineering) Christopher Smedberg (Computer Engineering) Project Advisors: Mohammad Tehranipoor (Dept. of Electrical and Computer Engineering) Omer Khan (Dept. of Electrical and Computer Engineering)

Project Statement: The counterfeit integrated circuit market is a major problem that can ruin company's reputations and lead to faulty products. The most common type of counterfeits are recycled IC's or IC's that have already been used but are sold as new. These used IC's may no longer function within specifications, or may not function properly. We will take advantage of the fact that an IC that is not genuine will almost always show some physical differences in its packaging.

Key Concepts: IC Counterfeiting Electron Microscopy Image Processing Blacktopping Remarking Re-Tinning Electron Microscopy Scanning Electron Microscope Material Analysis Image Processing MatLab Image Libraries Fingerprinting

IC Counterfeiting BlackTopping - Resurfacing technique used to remove signs of aging Remarking - Include blacktopping, but will be used to change type or quality of chip. Changes markings on chip Re-Tinning - During IC recycling, damage to the pins will most likely occurr. Re-tinning attempts to restore the pins to new quality

Electron Microscopy Scanning Electron Microscopes use a beam of electrons to scan the surface of something. The interaction of the electrons with the electrons in the object being imaged, give data about topography and composition We will use the SEM to gather highly detailed images of the IC's surface, and material analysis information of the chips capping material and pin material

Image Processing When examined at a higher magnification, the difference between genuine and counterfeit chips is very evident. This is due to sandblasting within the blacktopping process. GENUINE SUSPECT

Image Processing These images can be analyzed using a "black space" detection process. Genuine chip textures have a more well defined shape, and therefore less "black space" Counterfeit chip textures have more black space MATLAB can be used to enhance the images (so they can be compared), highlight the black spaces, and even count the amount of black pixels. This process is demonstrated on the genuine image from the previous slide.

Counterfeit Detection Test Lists and Descriptions

Basic Visual Test: This test will not be automated and will use a human's best judgement Using no magnification or very low-power magnification, the chip should be inspected for blatant defects, such as scratches or bent pins The Lot Codes and Number of pins should be checked to make sure they match as they should

Marking Permanency Test Test 1 - Using a mixture of 1 part alcohol, and 3 parts mineral spirits, use a cotton swab to rub this mixture over the surface of the chip. A color change, removal of markings or color may indicate a counterfeit IC Test 2 - Using Acetone, repeat the test as above. Acetone may also make a noticeable difference to the texture of the surface of a counterfeit chip

High Magnification Texture Test Using a highly magnified image of the suspect chips texture, this image will be compared to a similar image of a known good chip. Using image processing techniques, these images will be compared and it will be determined whether the image raises any questions This test takes advantage of the fact that most blacktopping techniques will show a different texture than genuine chips

Some Preliminary Results Number of highlighted spots ==>

Some Issues This method is not flawless In certain areas of the chip, a large black spot may show up (even if the chip is genuine- this would skew our results. Also, as shown in the previous slide, the amount of spots differs greatly between genuine chips (although it is MUCH higher in counterfeit) 'GENUINE1' has ~37,000 spots 'GENUINE2' has ~47,000 spots 'GENUINE3' has ~60,000 spots With more MATLAB trials, or with the incorporation of other enhancement commands, this value could be normalized We could focus on just the larger/smaller clumps of spots We could only look at the outline of the shapes etc...

Top and Bottom Texture Comparison This test will be very similar to the previous texture comparison test. however, the two images that will be compared will be of the Top and Bottom of the suspect chip Blacktopping may not be detected when comparing a suspect chip's texture to a known good chips. But comparing the top and bottom textures of the same chip may show more subtle differences. The black spot detection process in MATLAB can also be used to show differences between the top and bottom textures. If the "number of highlighted spots" is drastically different between the two sides, the chip is suspect.

Pin Re-Tinning Test Using the material analysis ability of the SEM, the material of the pin will be tested During counterfeiting, pins will be restored using a re-tinning process. Evidence of this process may be found when comparing the material analysis of a suspect chip to the material analysis of a known good chip

Surface Material Analysis The material analysis function of the SEM will also be used to find the chemical makeup of the chips surface. Blacktopping also uses a material different from what is used in the factories. The differences may be subtle, depending on the quality of the counterfeit, but can be observed when comparing the material analysis of the suspect chip to a known good chip

Counterfeit Classification Determining Counterfeit Type From Test Results

Counterfeit Taxonomy Using data collected from the tests we will run, we hope to be able to classify any found counterfeit chips appropriately

Possible Defects

Process Automation

Automated Tests Texture and Material Analysis test will run automatically once user has submitted required images Visual Inspection and Marking Permanency tests will need to be conducted by hand

Program Automation The testing process should run completely automatically, once the user has loaded the appropriate images. The user will be responsible for an image of the top texture, an image of the bottom texture, a material analysis of the pin, and a material analysis of the top of the suspect chip. User will also be required to submit an image of the top texture, a material analysis of a pin, and a material analysis of the top of a known good chip Program should automatically run tests and display any tests that raised concerns of the genuinity of the chip

MATLAB Server Can integrate with many applications and web service's allows matlab computations from custom applications Can use all existing MATLAB toolboxes for image processing Can be run remotely Cost: $500

Pixel Comparing Matches each pixel in an image looking for differences The corr2() function in MATLAB would be used to do the comparison. Would give the most accurate results Is highly dependent on alignment Alignment can be done with software

Project Timeline

Budget Available : $5,000 Estimate: $1,350 Purchased: Dremel Tool $150 To-be Purchased: De-capping service for 8051(X2) ~$150 FPGA(and decapping) ~$400-1000 Different Chip(and decapping) ~$300-400