Authentication Device Using Time-Dependent Defect Pattern Prediction
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Solution Overview
Problem
Existing authentication methods for IC cards and similar devices face challenges due to the deterioration of semiconductor chips over time, leading to changes in crystal defects and reduced authentication accuracy as the devices age.
Innovation Solution
An authentication system that acquires and predicts performance information, such as defective memory cell patterns, using a server and reader configuration to determine device authenticity based on the degree of agreement between actual and predicted defect patterns, ensuring accurate identification regardless of usage time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If factory-default distribution of crystal defects is used as authentication ID, then initial authentication accuracy is high, but authentication accuracy deteriorates as device usage time increases
Solution Approach 1:
The patent transforms the static authentication approach into a dynamic one by introducing time as a variable. The authentication system now accounts for the temporal evolution of defect patterns, where the expected defect distribution is updated based on elapsed time and usage history. This allows the system to adapt to natural deterioration while maintaining authentication accuracy.
Solution Approach 2:
The patent changes the parameter basis for authentication from fixed factory-default defect distribution to a time-dependent expected defect distribution. By modeling how defect patterns evolve over time and usage, the system adjusts the reference parameters dynamically, allowing accurate authentication even as the actual defect patterns change due to device aging.
2Reliability
If crystal defects are used for device identification, then unique device ID is obtained, but identification becomes difficult as defects increase with usage
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors and models the evolution of defect patterns over time. By using historical defect data and usage information to update the expected defect distribution, the system creates a feedback loop that compensates for the increasing complexity of defect patterns, maintaining reliable identification despite device aging.
3Measurement precision
If semiconductor chip is used for authentication, then identification function is provided, but authentication accuracy lowers as chip deterioration occurs
Solution Approach 1:
The patent applies preliminary action by pre-modeling the expected defect pattern evolution before authentication occurs. The system uses historical data and usage patterns to predict what the defect distribution should be at any given time, allowing it to accurately authenticate devices even before actual deterioration makes identification difficult.
Data Source
AI summary
According to an embodiment, an authentication device includes an acquiring unit, a predicting unit, and an authenticating unit. The acquiring unit is configured to acquire performance information of a first device that is a device to be authenticated. The predicting unit is configured to predict performance information of a second device that is a device being a reference for authentication according to a change with time from initial performance information. The authenticating unit is configured to perform an authentication process of determining whether or not the first device falls into the second device on a basis of a degree of agreement between the performance information acquired by the acquiring unit and the performance information predicted by the predicting unit.