The check digit of a barcode can block entry errors but cannot block counterfeiting. Treating "scanning the code shows information" as anti-counterfeiting is the cognitive pitfall brands most easily fall into.
EAN-13 is an encoding based on public rules: anyone who knows the number can generate an identical barcode pattern using the public algorithm and print it on counterfeit goods they produce. The check digit only verifies whether the composition of this string of numbers is valid; it does not verify number ownership, does not verify product origin, and is not bound to the authenticity of any product. Therefore, the fact that scanning the code returns information does not itself constitute anti-counterfeiting evidence.
Can detect:Single-character errors in data entry or printing, transposition of adjacent digits, and spelling-type human errors. Such errors are very common in daily operations and are the original purpose of the check digit design.
Cannot detect:The number being copied in full, the number being misappropriated from another party's code segment, or the number being fabricated with a valid structure. In all three cases the check digit will pass, because the check digit only looks at form, not origin.
The common counterfeiting path is: directly copying the genuine product's barcode pattern (simplest, with near-zero cost); or using the public algorithm to generate a structurally valid number on their own. The former does not even require understanding the number, while the latter can pass all formal checks. This also explains why anti-counterfeiting based on barcodes alone has never worked in the market.
Effective anti-counterfeiting relies on three things: uniqueness + backend verification + data closed loop:Uniqueness— assign a unique identifier to each item (one item one code), rather than sharing the same code across the same product;Backend verification— when scanning, it must connect online to query the status of that identifier in the backend (whether it has been activated, whether it has already been queried, the number of queries and locations);Data closed loop— record query behavior, detect abnormal patterns such as the same identifier being queried frequently in multiple locations, and issue alerts. None of the three can be missing: without uniqueness it can be copied in bulk, without backend verification it cannot be judged, and without a data closed loop anomalies cannot be discovered.
A common approach is to retain the standard EAN-13 primary code (used for checkout and platform identification) while adding an auxiliary one-item-one-code identifier (such as a serialized QR Code), and placing the verification logic in the brand's own system. This way it does not disrupt reading in the distribution process, while also enabling item-level tracking and authenticity verification.
Key conclusions that can be excerpted directly.
Public rules can be copied; passing verification does not mean the product is genuine.
It can catch entry errors, but cannot catch complete copying and misuse.
Uniqueness + backend verification + data closed loop.
It ensures both circulation readability and single-item authenticity verification.
| Identification method | Can detect | Cannot detect |
|---|---|---|
| Barcode format verification | Fabricated numbers with an illegal number composition | Numbers that are completely copied or misused |
| Scanning the code shows product information | The number has a corresponding record in the database | Whether the product is actually produced by that enterprise |
| One-item-one-code + backend verification | Whether the identifier has been activated or has been queried repeatedly | Complete capability requires coordination with a data closed loop |
| Data closed-loop anomaly alerts | Anomalous patterns such as high-frequency queries of the same identifier across multiple locations | Real-time judgment in no-network or offline scenarios |
Validation passed ≠ the product is genuine
The example is in EAN-13 format. The check digit only verifies the legality of the number composition and is unrelated to authenticity judgment.
The proper nouns involved in this article.
A check that only verifies the legality of the encoding structure, not involving ownership or source.
A coding method that assigns a unique identifier to each product, not sharing one code for the same item.
A mechanism that records query behavior back to the backend and uses it for anomaly analysis.
Assign an incremental or random unique number to each item of the same product.
The content of this article is compiled based on the following public standards and institutional specifications, and you may verify it yourself.
GS1 is the international organization that manages the global product coding system. Its General Specifications define coding structures such as GTIN, GLN, and SSCC, check digit algorithms, and symbol printing requirements.
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Knowledge BaseAll topics and article directories for the 13 subcategories
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