Countering the counterfeiters - a suitable case for blockchain
- The growing problem of counterfeit products turns out to be a legitimate use for blockchain.
In early July, U.S. Customs and Border Protection (CBP) agents inspected five shipments of what were ostensibly Apple AirPods shipped from China. In what is now a routine occurrence, the Cincinnati agents (presumably working out of the UPS Louisville hub, although this isn't specified) suspected something was amiss.
Whether it was the packaging, the $1,872 declared value or the Brownsville, Texas destination address handy to cartel smugglers, they flagged the shipment and sent the manifest and photographs to specialists at a CBP center designed to spot fakes. Instead of almost 6,400 AirPods and AirPods Pro models valued at more than $1.3 million retail they found counterfeit junk worth $312.
The Cincinnati seizure is just the tip of a huge iceberg of bogus consumer electronics, apparel, footwear and jewelry. Because of their high value-to-size, AirPods and other high-end earbuds have become particularly lucrative for counterfeiters. Indeed, already this year the CBP has seized about 360,000 counterfeit wireless headphones valued at more than $62 million., up 25-fold since 2019.
International e-commerce has been a boon to both consumers, who gain access to otherwise unavailable goods, and crooks who use sites like AliExpress, JD.com, Facebook, Amazon and Tokopedia to distribute their bogus wares. CBP statistics show the rise of such direct-to-consumer counterfeits via a significant rise in the number of small-parcel seized over the past decade, with most coming through the mail. In the preface to a 2020 U.S. Department of Homeland Security (DHS) report entitled Combating Trafficking in Counterfeit and Pirated Goods then-Secretary Chad Wolf wrote that:
Illicit goods trafficked to American consumers by e-commerce platforms and online third-party marketplaces threaten public health and safety, as well as national security. This illicit activity impacts American innovation and erodes the competitiveness of U.S. manufacturers and workers. Consumers must be confident in the safety, quality, and authenticity of the products they purchase online.
Whether measured by potential value or numbers, almost all counterfeits seized by the CBP come from China. Although 80% of the items are jewelry or apparel, the CBP confiscated more than $100 million in fake consumer electronics in 2019, with some estimating sales of phony AirPods to be upwards of $350 million per month. Indeed, the OECD estimates that fake goods now account for 3.3% of global trade.
Thwarting counterfeiters with blockchain
Blockchain has long seemed like a technology in search of a problem, but as I detailed earlier this year when describing features added to the Oracle database, Blockchain's immutability has many applications in securing and auditing enterprise data. Fighting counterfeiters is one area where blockchain might be useful by creating a permanent record of items as they travel through the supply chain.
Manufacturers have long used barcodes to automate the identification of item SKUs during distribution and at point-of-sale systems. Unfortunately, traditional UPC markers don't support item-level identifiers and can be easily forged. In contrast, newer GS1 Global Trade Item Numbers (GTIN) support serialization to uniquely identify individual items. As an Auburn University RFID Lab report details, SGTINs can be encoded in print as QR codes or 2D Data Matrices and electronically as RFID or NFC tags and automatically read using image or RF scanners.
Whereas SGTIN is a way to uniquely tag and automatically identify individual items, blockchain provides a mechanism to authoritatively and irrefutably track items as they make their way through the supply chain. Here's how the Auburn report sees the combination of unique identifiers and blockchain being used to fight counterfeit products.
"With blockchain, brands can combat counterfeiting by maintaining immutable records of all commissioned products and by sharing item-level detail with vendors and consumers to ensure the authenticity of goods. ...By documenting and distributing the identities of legitimate goods, a brand owner can crackdown on counterfeit goods being produced upstream and supplement product verification efforts with retail partners and patrons downstream. By using item-level information to empower data-driven decisions, illegitimate distribution channels can be identified and bad actors can be severed from the supply network.
It also sees the blockchain distributed ledger being used to resolve disputes over product legitimacy between buyers and sellers:
In a blockchain ecosystem where brand owners and retailers exchange item-level data related to shipments and orders, disputes can be settled with hard data and resolutions can be expedited because both parties are referencing the same source of information made available by the distributed ledger.
Item-level blockchain-based product traceability can also improve:
- Food and drug safety by identifying particular items suspected of contamination and flagging bogus or gray-market products.
- Claims adjudication of mis-shipments and inaccurate order fulfillment.
- Lost inventory or product shrink by minimizing ambiguity or intentional decept in business processes.
- Supplier audits and scorecards by providing indisputable proof of timely delivery and product provenance.
Products from Consensys, SAP and Vi3 now incorporate blockchain technology to reduce the distribution and automate the identification of counterfeit goods.
Using AI to spot fakes
Using overt — QR codes, RFID tags — and covert — microscopic taggants, physical unclonable functions, aka PUFs — to verify product authenticity are effective, but can be expensive or impractical for non-packaged goods like apparel or jewelry. High-resolution image analysis using AI models is an alternative increasingly used by fashion retailers and manufacturers. Pioneered by startups like Entrupy, the process combines machine learning, computer vision and a massive image database of both authentic and counterfeit products.
For example, the Entrupy system uses a high-resolution camera that magnifies images by at least 100-times to expose product characteristics such as the fabric, texture and finish in much more detail than would be apparent to the human eye. Then, much like facial recognition systems such as Apple FaceID, the system creates a digital ID of an original item using 500 to 1,500 features. Individual articles are then compared with this digital fingerprint to verify their authenticity and flag counterfeits.
According to a paper detailing the technique, the Entrupy system has several benefits over conventional tagging (emphasis added):
We do not need to embed any substance within the product or object. Our technique is non-invasive and does not modify the object in any way. ii) There is no need to tag every single item. We can classify original and duplicate based on the microscopic variations. iii) Current overt/covert authentication techniques cannot authenticate objects there were not tagged earlier. In our case, since we use machine learning techniques, we can authenticate new instances of the object. iv) Most of techniques such as nano-printing, micro-taggants are expensive to embed onto the product. Plus their detection based on specialized, expensive microscopic handheld devices which is a problem in consumer/enterprise adoption. Our device and cloud based authentication solution that works with a mobile phone is low cost and simple to use.
Counterfeits are both a significant risk to brand reputation and an increasing cost due to lost revenue. Since apparel is the primary target of bogus products, it's not surprising that luxury and highly visible brands like Calvin Klein, Chanel, Gucci, Levi's, Lululemon and Nike are already using technology like RFID tags and AI image recognition to verify legitimate products and block counterfeiters.
Amazon Project Zero is perhaps the most ambitious project to eliminate counterfeits by allowing brands to tag each unit with a unique code, shared with Amazon, which enables it to scan and confirm the authenticity of every enrolled product sold through Amazon’s store. While Amazon appears to be using a centralized database rather than a distributed blockchain ledger, expect manufacturers to investigate blockchain as they seek a generalized product verification system that works throughout their supply chain.