PUF Key Extraction Using Variance-Based Quantization
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Solution Overview
Problem
In the production of Physical Uncloneable Function (PUF) devices, such as those with dielectric particle coatings, deriving uniformly distributed cryptographic keys is challenging due to non-uniform capacitance value distributions across multiple devices, requiring costly measurement and programming of quantization levels for each device.
Innovation Solution
A method and device that measure variance in physical parameters to determine quantization intervals, allowing for the derivation of data sets without the need for extensive testing and programming, enabling self-calibration and efficient production by calculating interclass and intraclass variances to ensure uniform key distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If quantization levels are determined by measuring and programming each device individually, then uniform key distribution is achieved, but production cost and complexity increase significantly
Solution Approach 1:
The device performs self-calibration by autonomously measuring its own capacitance values and determining quantization levels without external intervention. The processor calculates interclass and intraclass variances and programs the quantization levels directly into memory, eliminating the need for costly external measurement and programming equipment while achieving uniform key distribution.
Solution Approach 2:
The patent changes the approach from individual device measurement to statistical parameter estimation. By measuring a small sample of devices and calculating variance parameters (interclass and intraclass), the system derives quantization levels that work for the entire production batch, reducing measurement complexity while maintaining manufacturing precision.
2Measurement precision
If extensive testing and programming is performed for each device, then quantization accuracy is improved, but production time and cost increase
Solution Approach 1:
The system performs preliminary measurements on a small sample of devices during the design phase to estimate variance parameters. These pre-calculated quantization levels are then applied to all production devices without individual measurement, significantly increasing production speed while maintaining sufficient quantization accuracy through statistical modeling.
Solution Approach 2:
Instead of measuring each device individually, the patent creates a statistical model (copy) of the device population based on sample measurements. The quantization levels derived from this model are then applied universally across all devices, achieving high productivity while maintaining measurement precision through the accuracy of the statistical model.
3Reliability
If capacitance values are quantized into equiprobable intervals, then cryptographic key uniformity is achieved, but device complexity increases due to variance calculation requirements
Solution Approach 1:
The patent transforms the complex problem of determining equiprobable quantization intervals into a simpler parameter-based solution. By calculating just two variance parameters (interclass and intraclass) from sample data, the system derives quantization levels that achieve cryptographic key uniformity without requiring complex real-time calculations or additional hardware components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach eliminates the need for extensive testing and programming, reducing production costs and enabling efficient derivation of uniformly distributed cryptographic keys, enhancing security by ensuring all possible keys have equal probability, thus improving key generation efficiency and robustness.
Implementation Method 1
Sensor elements are arranged at a top metal layer of the IC to locally measure capacitance values at different coating positions
Data Source
AI summary
The present invention relates to a method and a device (11) using a physical token (14), which provides measurable parameters, to derive at least one data set. A plurality of values of one or more of the parameters are measured. From these measured values, a measure of variance is calculated. Quantization intervals into which a measured value is to be quantized are then determined. A possible value of a data set, which subsequently can be derived from a measured value provided by the physical token, is associated with each quantization interval. Further, information which subsequently enables determination of these quantization intervals is stored. Hence, an enrolling phase has been completed. When the preparing phase has been completed, a deriving phase may commence. When a data set is to be derived, for example to be used as a cryptographic key, a value of any one of the parameters provided by the PUF is measured. This measured value is quantized into a determined quantization interval, and a data set may be derived from the quantization interval into which the measured value is quantized.