Digital Fingerprint Authentication for Physical Objects
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Solution Overview
Problem
Current methods for identifying and authenticating physical objects rely on extrinsic identifiers that are prone to damage, loss, counterfeiting, and high production costs, and fail to detect counterfeit or unknown objects effectively.
Innovation Solution
The use of digital fingerprints, generated from the object's inherent structure, eliminates the need for extrinsic identifiers by creating a unique digital signature that can be stored and retrieved for authentication, utilizing feature extraction algorithms to reduce data to a manageable set of features for efficient processing and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extrinsic identifiers (labels, tags, RFID) are applied to objects for identification, then object identification capability is improved, but manufacturing costs increase and reliability deteriorates due to damage, loss, and counterfeiting risks
Solution Approach 1:
The object itself serves as the identifier through its inherent structural features. The digital fingerprint is extracted from the object's own geometry, surface characteristics, or material properties, eliminating the need for external identifiers. This self-service approach reduces manufacturing costs while improving reliability since the identification capability is intrinsic to the object and cannot be lost or damaged separately from the object itself.
Solution Approach 2:
The identification information is extracted from the object's inherent structure rather than being applied to it. Feature extraction algorithms identify and isolate unique structural characteristics that serve as the digital fingerprint. This extraction process converts the object's physical attributes into identification data without adding extrinsic elements, thereby reducing manufacturing costs and eliminating the vulnerabilities associated with applied identifiers.
2Reliability
If extrinsic identifiers are applied to objects, then identification capability is improved, but the identifiers themselves are vulnerable to damage, loss, stealing, duplication, and counterfeiting
Solution Approach 1:
The object's inherent structure serves as the security credential. Since the digital fingerprint is derived from the object's own physical characteristics, any attempt to separate the identifier from the object (theft, loss, damage) is inherently prevented. The identification capability is bound to the object itself, making it impossible to steal or lose the identifier independently.
Solution Approach 2:
The natural variations and imperfections in object manufacturing, which traditionally represent defects or inconsistencies, are converted into security features. These unique structural variations become the basis for the digital fingerprint, making each object inherently distinct and unforgeable. The very characteristics that make objects imperfect also provide the security against counterfeiting.
3Measurement precision
If comprehensive object features are captured for authentication, then authentication accuracy is improved, but data processing complexity and storage requirements increase
Solution Approach 1:
Feature extraction algorithms selectively identify and isolate the most discriminative structural characteristics from the complete set of object features. Rather than processing all possible data, the system extracts only the essential features that provide sufficient authentication accuracy. This extraction reduces data dimensionality while maintaining identification precision, thereby simplifying processing and storage requirements.
Solution Approach 2:
Different regions or aspects of the object are analyzed with different levels of detail based on their discriminatory value. Critical features that provide high authentication value are captured with greater precision, while less significant features are processed with lower complexity. This localized approach to feature analysis optimizes the balance between authentication accuracy and processing complexity.
Data Source
AI summary
A system may include an event trigger processor (ETP) configured to receive signals from sensors or another system (FIG. 11). Output signals from the sensor(s), local or remotely located, may be utilized by the ETP as trigger inputs to initiate a process or response, namely authentication actions, which also may be local or remote from the ETP. Events from external systems also may serve as trigger inputs to the ETP. In some embodiments, as a triggered response, the ETP may direct a local field imaging system to acquire an image of an object, generate a digital fingerprint from the image, and query a database using the generated digital fingerprint to identify or authenticate the object. The ETP may initiate or direct various actions by sending a message to another entity or system, for example, using known network communication protocols.