Component Counterfeiting: On the Verge of a Future Without Fakes?
By Murray Slovick
For all its high-tech advances, the semiconductor industry has been extremely vulnerable to counterfeits, which pose an estimated $200 billion risk per year to the global electronics supply chain. Global chip shortages make this risk even greater. A shortage of components will push purchasers towards the grey market and increases the importance of identification to verify ownership of a device. What is more, trade in counterfeit and pirated goods has risen steadily since the COVID pandemic began, with microelectronics being one sector on the rise.
Gone are the days when a fake component was easy to spot. Components can now be cloned precisely and it is difficult to distinguish them from the genuine article. Despite numerous available anti-counterfeiting techniques such as RFID labels and holograms, semiconductor devices can be copied. Therefore, the development of new approaches and improvement of current technologies is of urgent need.
Let’s look at some of the so-called “unbreakable” product authentication methodologies that promise to make counterfeiting much more difficult.
Physically Unclonable Functions and Quantum Dots
Every chip is unique, thanks to random, uncontrollable microscopic imperfections in the molecular structure of the material used to produce the chip. This uniqueness can be used to prove authenticity. Physically unclonable functions (PUFs) make use of these natural random fluctuations. A PUF is a device that has unique and non-repeatable physical properties that can be translated into usable bits of information. PUFs which use random physical characteristics for authentication are advantageous over existing optical solutions, such as holograms, due to the inherent asymmetry in their fabrication and reproduction complexity. Authentication based on PUFs comprises a chip manufactured by intrinsically random processes that make cloning almost impossible. Because the PUF system is hard to duplicate, this method can ensure a very high degree of security, making it well-suited for anti-counterfeiting applications.
Quantum dots (QDs) are semiconductor nanoparticles that exhibit high efficiency photoluminescence over a wide range of tunable colors, making them effective at imparting unique optical properties. Security features based on QDs are therefore inherently very difficult to reproduce and can be used to combat counterfeiting. A randomly deposited array of quantum dots can be encapsulated in a transparent polymer, forming a tag. Quantum computers use light rather than electric charges to store and carry information. According to the laws of quantum mechanics, a single photon can reside in two different places at the same time. As such an individual photon can act as a quantum bit, or qubit, which carries much more information than a binary bit, which is limited to a value of 0 or 1.
As an example, Ubiquitous Quantum Dots, or UbiQD, a New Mexico-based nanotechnology company, and SICPA SA, a Swiss technology company specializing in security inks, have expanded their partnership in the development of anti-counterfeit security inks based on UbiQD’s quantum dot technology. This partnership will enable development of cutting-edge optical and machine-readable features in the form of a portfolio of security inks.
At the same time, researchers at the National Institute of Standards and Technology (NIST) and their colleagues have connected microchip quantum dots with miniature waveguides (circuits that can guide the light) without significant loss of intensity. The hybrid circuit consists of two components, each initially built on a separate chip. The first is a gallium arsenide semiconductor device designed and fabricated at NIST, which hosts the quantum dots and directly funnels the single photons they generate into a second device, a low-loss silicon nitride waveguide developed at UCSB.
The scientists, who include researchers from the University of California, Santa Barbara (UCSB); the Massachusetts Institute of Technology (MIT); the Korea Institute of Science and Technology and the University of São Paulo in Brazil, reported their findings December 11 in Nature Communications.
Quantum Base Ltd., spun-out from Lancaster University, has invented, developed and patented a portfolio of nanoscale quantum security devices driven from development of both Optical (OPUF) and Electronic (EPUF) versions, and a simple quantum random number generator (Q-RAND). Their other two products, Q-ID Electronic and Q-ID Optical, both enable end-user authentication, anti-counterfeit device tagging, identity card authentication, verification of pharmaceuticals and other applications.
The AS6081 standard was created in response to a significant and increasing volume of fraudulent/counterfeit electronic parts entering the aerospace supply chain, posing significant performance, reliability and safety risks. The AS6081 standard establishes requirements and practices to mitigate the risk of buying, receiving and selling fraudulent/counterfeit parts, therefore giving customers confidence in their own supply chain. AS6081 is a base standard in ANAB’s (the ANSI National Accreditation Board) roster. ANAB is a non-governmental organization that provides accreditation services and training to public- and private-sector organizations, serving the global marketplace
In an effort to automate the External Visual Inspection and Electrical Testing requirements of the AS6081 counterfeit prevention standard, companies such as the Albuquerque-based startup Chiplytics promise faster turnaround and more data-driven assessments. Chiplytics’ proprietary technology, the Chiplytics One, screens every chip going into critical systems to fight counterfeiting, ensuring safety and compliance of semiconductors worldwide, which allows commerce and exchange to function securely around the globe.
It does so via an automated semiconductor quality assurance product for any semiconductor collecting both a unique electrical signature and image of each chip to perform an analysis to determine if a chip is both authentic and error-free. It’s also the first inspection platform that combines electrical and optical testing to build data sets to detect small differences to identify clones, counterfeits or damaged chips. The company plans to leverage these data sets and their proprietary software to help companies source and test chips before they get put into high-reliability systems, saving them from costly recalls and building trust. Chiplytics performs the testing non-invasively, detecting anomalies using machine learning. The product uses Power Spectrum Analysis (PSA) to extensively evaluate homogeneity and identify outliers. Data acquisition is performed within milliseconds with minimal setup, enabling greater coverage and higher throughput.
Terahertz radiation, whose wavelengths lie between those of microwaves and visible light TeraHertz (THz) waves are transparent to nonconductive materials frequently used for the encapsulation of devices such as semiconducting chips. Utilizing this fact, researchers from Korea’s Ajou University and Panoptics Corp. developed a rapid three-dimensional (3D) time-of-flight imaging tool for inspection of packaged semiconductor chips, using terahertz (THz) time-domain spectroscopy techniques. By also using phase information, they are able to detect and identify defects in the packaged chip.
Artificial Intelligence (AI)
The principal challenge in counterfeit electronics is finding them. To that end, Israeli startup, Cybord, has a solution that is software only; it uses hardware already on the line to source images of the parts being used from the top and the bottom. Those images are analyzed by AI software using an extensive database, allowing the company to detect if a part is fake, damaged, corroded, miss-marked or contains any other anomaly. Even when the part is perfect, the company records where every part is placed and into which PCB or product it ends up in and checks for counterfeit parts during product assembly.
Cybord’s software solutions monitor placements on SMT lines in real time and eliminate the use of nonconforming electronic components during product assembly while arming OEMs with visibility and traceability. Using artificial intelligence and big data, component defects are addressed during placement and before reflow, simplifying rework and improving product reliability.
AI has advanced to the point where it can identify these fake parts. Cybord’s visual software verifies the authenticity of each component through its measurements, date code, lot code and batch. The challenge, of course, is finding sufficient data. Cybord claims to have compiled data for billions of electronic parts in its database, analyzing about 250 million components a month.
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