Anti-Counterfeit Method Using Biometric Key Segmentation
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Solution Overview
Problem
Current anti-counterfeiting methods for two-dimensional bar codes are inadequate as they lack robust authentication and are easily recognizable, making them susceptible to counterfeiting, and existing random number generators used for secret keys do not ensure secure key generation.
Innovation Solution
An anti-counterfeit method that uses fingerprint data to generate a random feature secret key, comprising a first sub secret key encoded into a micro-texture image and a second sub secret key embedded in an encryption program, which is used to encrypt raw data and create an information code image that can only be decrypted if the image sensor successfully integrates the sub secret keys, thereby enhancing authentication and preventing counterfeiting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a two-dimensional bar code is used to store item information for automatic recognition, then information retrieval efficiency is improved, but the code becomes easy to recognize and counterfeit, resulting in poor anti-counterfeit function
Solution Approach 1:
The secret key is divided into two parts: the first part is embedded in the information code image (visible to readers), while the second part is stored in the authentication device. This segmentation allows efficient recognition while preventing counterfeiting, as the complete key cannot be obtained by simply reading the code.
Solution Approach 2:
An authentication device serving as an intermediary is introduced between the information code and the verification process. This device holds the second part of the secret key and performs authentication by combining it with the first part from the code, enabling both efficient retrieval and reliable anti-counterfeiting.
2Reliability
If a random number is used as the secret key for encryption, then decryption security is improved, but the authentication problem of who generates the random number remains unsolved
Solution Approach 1:
The authentication device performs preliminary verification by checking whether the submitted first part of the secret key matches the expected value before proceeding with decryption. This preliminary action solves the authentication problem without requiring complex verification processes.
3Ease of operation
If the first part of the secret key is embedded in the information code image for easy reading, then recognition convenience is improved, but the code becomes more susceptible to counterfeiting
Solution Approach 1:
The secret key is segmented into two parts with different distribution locations. The first part is placed in the information code image for convenient reading, while the second part remains in the authentication device. This segmentation maintains recognition convenience while preventing counterfeiting, as the complete key cannot be reconstructed from the code alone.
Data Source
AI summary
An anti-counterfeit method includes: obtaining raw data to be encoded; collecting fingerprint data by analogue acquisition to obtain initial fingerprint feature information and encrypting the initial fingerprint feature information to obtain a random feature secret key, the random feature secret key comprising a first sub secret key and a second sub secret key and the first sub secret key is encoded into a micro-texture image while the second sub secret key is embedded in an encryption program; encrypting, through the random feature secret key, the raw data to be encoded to generate an information code image, the information code image comprising the micro-texture image; passing an anti-counterfeit authentication when an image sensor succeeds in integrating the first sub secret key and the second sub secret key to generate the random feature secret key; and succeeding in decrypting, by the image sensor, the information code image through the random feature secret key.