Counterfeit components have been defined as a growing concern in recent years as demand increases for reducing costs. In fact the Department of Commerce has identified a 141% increase in the last three years alone. A counterfeit is any item that is not as it is represented with the intention to deceive its buyer or user. The misrepresentation is often driven by the known presence of defects or other inadequacies in regards to performance. Whether it is used for a commercial, medical or military application, a counterfeit component could cause catastrophic failure at a critical moment. The market for long life electronics, based on commercial off the shelf (COTS) parts, such as those used in medical, military, commercial depot repair, or long term use applications (e.g. street and traffic lights, photovoltaic systems), seems to create a perfect scenario for counterfeiters. With these products, components wear out and need to be replaced long before the overall product fails. The availability of these devices can be derived in many ways. For example, a typical manufacturer may render a component obsolete by changing the design, changing the functionality, or simply discontinuing manufacture. Also, the parts that are available after a design has been discontinued are often distributed by brokers who have very little control over the source or supply. Recycling of devices has also emerged as a means of creating counterfeit devices that are presented as new. And finally, as demand and price increase, the likelihood of counterfeits also increases. This paper will address the four unique sources of counterfeit components and insight into how they occur. Detection methodologies, such as visual inspection, mechanical robustness, X-Ray, XRF, C-SAM, Infrared Thermography, electrical characterization, decapsulation, and marking evaluations, will be compared and contrasted, as well as multiple examples of counterfeit parts identified by DfR.

Counterfeiting of electronic components continues to be an evolving issue that greatly impacts many companies around the globe. And with so many initiatives that have either been enacted or are in the works, there is a significant amount of confusion and even fear in our industry. The financial impact and potential loss of life related to counterfeit components has become so great that an enormous amount of attention is now being devoted to identifying and mitigating this risk by both private industry and governments agencies around the world. Many companies are reaching out to test labs for both the testing of their components and direction on how to address some of these issues. This paper addresses a few of the questions that our lab is getting from some of our customers regarding counterfeit IC’s and how we have answered those questions. The goal is to provide some additional insight to allow others to address this issue proactively and without fear.

Counterfeiting is an increasing concern for businesses and governments as greater numbers of counterfeit integrated circuits (IC) infiltrate the global market. There is an ongoing effort in experimental and national labs inside the United States to detect and prevent such counterfeits in the most efficient time period. However, there is still a missing piece to automatically detect and properly keep record of detected counterfeit ICs. Here, we introduce a web application database that allows users to share previous examples of counterfeits through an online database and to obtain statistics regarding the prevalence of known defects. We also investigate automated techniques based on image processing and machine learning to detect different physical defects and to determine whether or not an IC is counterfeit.

It is known by both the commercial and government suppliers, one of the best ways to guarantee the security and reliability of IC's is to image the IC directly using an x-ray microscope. These images can be inspected for many signs of counterfeit electronics. Unfortunately, previous generations of x-ray imaging systems have not kept up with the increasingly sophisticated counterfeiting techniques. Traditional 2D X-ray inspection techniques are becoming inadequate for imaging and verifying features due to the limited resolution of these systems for thick samples and because 2D images contain too many overlapping features to easily discern, making identification very difficult. This paper discusses the development of advanced sample preparation techniques for counterfeit IC detection. It presents information on the limitations of X-ray imaging and 3D tomographic reconstruction, and on the models for resolution configuration improvement.

Possible methods for counterfeit electronic part detection can be classified into two main categories: physical inspection and electrical testing. The physical inspection techniques can potentially be extended to different integrated circuit (IC) types; however, there are some challenges. The major contribution of this paper is to tackle these issues by introducing and optimizing two novel three and four dimensional imaging techniques that can provide us with the necessary information on interior and exterior geometry along with the material composition for the parts under test: four-dimensional scanning electron microscopy and dual energy 3D x-ray microscopy. In this study, advanced image processing and image analysis tools are utilized to establish a more consistent and accurate image perception. Inconsistencies within the samples and their defects are also used as an alternative to having a golden IC. However, the final decision has further been validated using results from five known authentic samples.

Battelle has developed a technology to nondestructively classify electronic components as authentic or counterfeit. The technology uses a method that creates feature vectors for each class of devices using a reconfigurable side channel power analysis test fixture. This test fixture monitors the power fluctuations of the device either via connection to a power or a ground pin while test signals are sent to the device. Power waveforms are processed, undergo dimensionality reduction techniques, and the resultant data is plotted in Principal Component Analysis (PCA) space to reveal information related to the authenticity of the device under test. To scale this technology to the full catalog of parts available to a production test house, unique tools have been created that provide automated test generation and scoring of feature vectors.

As counterfeiting techniques and processes grow in sophistication, the methods needed to detect these parts must keep pace. This has the unfortunate effect of raising the costs associated with managing this risk. In order to ensure that the resources devoted to counterfeit detection are commensurate with the potential effects and likelihood of counterfeit part usage in a particular application, a risk based methodology has been adopted for testing of electrical, electronic, and electromechanical (EEE) parts by the SAE AS6171 set of standards. This paper provides an overview of the risk assessment methodology employed within AS6171 to determine the testing that should be utilized to manage the risk associated with the use of a part. A scenario is constructed as a case study to illustrate how multiple solutions exist to address the risk for a particular situation, and the choice of any specific test plan can be made on the basis of practical considerations, such as cost, time, or the availability of particular test equipment.

Counterfeit electronics constitute a fast-growing threat to global supply chains as well as national security. With rapid globalization, the supply chain is growing more and more complex with components coming from a diverse set of suppliers. Counterfeiters are taking advantage of this complexity and replacing original parts with fake ones. Moreover, counterfeit integrated circuits (ICs) may contain circuit modifications that cause security breaches. Out of all types of counterfeit ICs, recycled and remarked ICs are the most common. Over the past few years, a plethora of counterfeit IC detection methods have been created; however, most of these methods are manual and require highly-skilled subject matter experts (SME). In this paper, an automated bent and corroded pin detection methodology using image processing is proposed to identify recycled ICs. Here, depth map of images acquired using an optical microscope are used to detect bent pins, and segmented side view pin images are used to detect corroded pins.

This paper explains the CLSM technique and presents surface roughness measurement data from several groups of known authentic and suspect counterfeit parts. Surface roughness is an important characteristic of plastic encapsulated or metal lidded parts because counterfeit parts are often blacktopped or re-polished and remarked.

The Society of Aerospace Engineers (SAE) AS6171 Aerospace Standard standardizes the test and inspection procedures, workmanship criteria, and minimum training and certification requirements to detect counterfeit electrical, electronic, and electromechanical parts. The standard comes in response to a significant and increasing volume of counterfeit electrical, electronic, and electromechanical parts entering the supply chain. This short manuscript and its accompanying talk update the audience on the risk based methodology for detecting potential counterfeiting related defects. The techniques that are discussed in AS6171 slash sheet include film radiography and filmless radiography such as digital radiography, real time radiography, and computed tomography. The analysis is performed on parts to verify that the internal package or die construction is consistent with an exemplar item. AS6171 will provide the counterfeit detection community with standardized test and inspection procedures, workmanship criteria, and minimum training and certification requirements to detect counterfeit electrical, electronic, and electromechanical parts.

This presentation is chronologically-progressive to the author's ISTFA Keynote given in 2010: "Counterfeiters' Techniques: Constantly Improving to Avoid Detection - National Security Depends on Us to Keep Up". It shares, in detail, the forensic test methodologies utilized by SMT and ultimately the research breakthroughs which gave the labs crystal-clear insight into the counterfeiters specific step-by-step rework process. The presentation includes all forensic work utilized in exposing the "Micro-blast" & "Flat-Lap" counterfeit processes identified at SMT labs during 2011, as well as unpublished novel process threats and refinements identified in 2013 & 2014. It also covers the counterfeit mitigation work that SMT supported with the GAO and Senate Armed Services Committee's investigation into counterfeits within DoD supply chains during the 2011-2012 time period.

The entire electronics industry is now facing a much more insidious counterfeit threat than at any time in the past. The existence of cloned electronic components bearing the markings of major component manufacturers in today’s global supply chains has been clearly established within SMT’s labs over the past 3 years. The most worrisome aspect of these “made from scratch” fakes is their ability to easily pass current Industry-Standard counterfeit inspection processes and electrical testing to the manufacturers’ data sheet. My presentation will focus on several actual examples of this most concerning advanced counterfeiter capability and some of the processes utilized by SMT as an obsolescence component supplier and testing lab to mitigate this new and growing threat from making it to our OEM & CM customers.

The drive towards miniaturization has created increasing challenges to the overall failure analysis and quality inspection of electronic devices. This trend has equally challenged the image quality of x-ray inspection systems – engineers need to see more details in each inspection. Image quality is paramount to the ability of making actionable decisions on the information acquired from an x-ray machine. Previous generations of x-ray technologies have focused on hardware improvements – better x-ray sources and better x-ray sensors. Although further improvements can still be achieved in hardware, our focus will be on the latest wave of technology breakthroughs and innovation in radiography systems: algorithms.

This presentation demonstrates how Time-of-Flight Secondary Ion Mass Spectroscopy provides unique information to identify suspect counterfeit semiconductor devices. An example is shown where the epitaxial layers of a light emitting device (LED) do not match those of the exemplar. Keywords: Secondary Ion Mass Spectroscopy, SIMS, counterfeit detection, LED, Light emitting diode.

This paper evaluates several approaches for automating the identification and classification of logos on printed circuit boards (PCBs) and ICs. It assesses machine learning and computer vision techniques as well as neural network algorithms. It explains how the authors created a representative dataset for machine learning by collecting variants of logos from PCBs and by applying data augmentation techniques. Besides addressing the challenges of image classification, the paper presents the results of experiments using Random Forest classifiers, Bag of Visual Words (BoVW) based on SIFT and ORB Fully Connected Neural Networks (FCN), and Convolutional Neural Network (CNN) architectures. It also discusses edge cases where the algorithms are prone to fail and where potential opportunities exist for future work in PCB logo identification, component authentication, and counterfeit detection. The code for the algorithms along with the dataset incorporating 18 classes of logos and more than 14,000 images is available at this link: https://www.trusthub.org/#/data .

PCB assurance currently relies on manual physical inspection, which is time consuming, expensive and prone to error. In this study, we propose a novel automated segmentation algorithm to detect and isolate PCB components called EC-Seg. Component segmentation and localization is a vital preprocessing step in the automation of component identification and authentication as well as the detection of logos and text markings. As test results indicate, EC-Seg is an efficient solution to automate quality assurance toolchains and also aid bill-of-material (BoM) extraction in PCBs. It also has the potential to be used as a region proposal algorithm for object detection networks and to facilitate sensor fusion involving artifact removal in PCB X-ray tomography.

The electronics supply chain is being increasingly infiltrated by non-authentic, counterfeit electronic parts, whose use poses a great risk to the integrity and quality of critical hardware. There is a wide range of counterfeit parts such as leads and body molds. The failure analyst has many tools that can be used to investigate counterfeit parts. The key is to follow an investigative path that makes sense for each scenario. External visual inspection is called for whenever the source of supply is questionable. Other methods include use of solvents, 3D measurement, X-ray fluorescence, C-mode scanning acoustic microscopy, thermal cycle testing, burn-in technique, and electrical testing. Awareness, vigilance, and effective investigations are the best defense against the threat of counterfeit parts.

Counterfeit parts are marketed with the intent to deceive the customer. This intent to deceive defines a counterfeit part and separates it from faulty parts, which have defects that are unknown to the manufacturer or distributor. This paper presents three cases in which counterfeit electronic parts were assembled into hardware items and later found to be faulty in some manner. Laboratory techniques used to identify these parts as counterfeits are presented. Non-laboratory techniques that could have prevented the parts from entering service in these cases are also described. Techniques to combat counterfeit parts range from very simple observation of the parts and the paperwork to failure analysis carried out in a laboratory environment. In all of these cases, the potential existed to detect the counterfeit parts prior to assembly into hardware and prior to field deployment of the defective devices.

The counterfeiting of semiconductor devices has become an important contributor as more components are used in the increasingly sophisticated audio and navigation systems while more suppliers are moving manufacturing plants off-shore. This paper presents a case study on how the authors were able to identify a counterfeit device and certify a replacement source. In this study, failed devices with Intersil CA3080 Operational Transductance Amplifier IC from factory testing and field returns in suspect lot codes were purchased from a second source, due to the unavailability of the obsolete device from the regular first source. The suspect lot codes that were not recognizable by the manufacturer were determined to be counterfeit devices. Many pieces of physical evidence suggested that the failed devices were not consistent with genuine devices directly purchased from the manufacturer.

This abstract provides an introduction to the utility of botanical DNA taggants to provide supply chain security for electronic components and to protect against counterfeiting and diversion. A detailed treatment of the science behind Applied DNA Sciences' botanical DNA technology, its applications to semiconductors and microchips, and an overview of DNA analysis by PCR and CE analysis is provided. In addition, information on the evolution of electronic product counterfeiting and inadequate anti-counterfeiting measures is also provided.