PUF Element Pairing for Stable Key Generation
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Solution Overview
Problem
Existing PUF systems face a trade-off between utilization rate and stability, where selecting PUF elements based on mismatch polarity to minimize environmental effects leads to discarding a significant portion of useful elements, resulting in unstable crypto keys and reduced overall utilization.
Innovation Solution
A method involving pairing and recursive pairing of PUF elements to generate stable key bits, where mismatch values are sorted and paired to create random, large difference values, reducing the impact of environmental changes and maintaining high utilization rates by converting Gaussian distributions into bi-modal distributions with increased separation margins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PUF elements are selected based on mismatch polarity to minimize environmental effects, then stability of generated key bits is improved, but utilization rate of PUF elements deteriorates due to discarding a significant portion of elements
Solution Approach 1:
The PUF element population is segmented into multiple groups based on mismatch magnitude categories. Elements are divided into first groups (high mismatch, stable) and second groups (low mismatch, unstable). By segmenting the population and applying different handling strategies to different segments, the system can utilize more elements while maintaining stability through selective pairing across segments.
Solution Approach 2:
The system creates composite PUF elements by pairing elements from different mismatch magnitude groups. Each composite element combines a first PUF element from a first group with a second PUF element from a second group. This composite structure allows the system to benefit from both high-mismatch stability and low-mismatch utilization, achieving both reliability and productivity goals simultaneously.
2Measurement precision
If PUF elements with little mismatch are excluded to prevent unstable key bits, then accuracy of generated key bits is improved, but quantity of usable PUF elements deteriorates
Solution Approach 1:
The system performs preliminary classification of PUF elements into multiple groups based on mismatch magnitude before key generation. Elements are pre-sorted into first groups (high mismatch) and second groups (low mismatch). This preliminary action enables the subsequent pairing process to systematically combine elements from different groups, ensuring accuracy is maintained while maximizing the quantity of usable elements through structured pre-processing.
Solution Approach 2:
The system changes the parameter of mismatch magnitude by selecting and pairing elements from different mismatch categories. Instead of using elements with a single fixed mismatch characteristic, the system varies the mismatch parameters across paired elements, combining high-mismatch and low-mismatch elements to create composite structures that achieve both accuracy and quantity goals.
3Stability of the object's composition
If a large portion of PUF elements is discarded to achieve desired bit error rate, then stability is improved, but overall utilization rate deteriorates
Solution Approach 1:
The system merges PUF elements from different mismatch magnitude groups into composite elements. By combining first PUF elements (high mismatch) with second PUF elements (low mismatch) in structured pairs, the system achieves stability through the high-mismatch components while utilizing the low-mismatch components that would otherwise be discarded. This merging approach improves overall utilization rate while maintaining stability.
Solution Approach 2:
Instead of permanently discarding low-mismatch PUF elements, the system recovers their utility by pairing them with high-mismatch elements from first groups. The low-mismatch elements are not discarded but rather repurposed as complementary components in composite PUF elements, where they provide additional functionality while the high-mismatch partners ensure stability. This recovery approach maximizes utilization while maintaining stability.
Data Source
AI summary
Systems and methods allow to take advantage of the natural statistical variation of physical properties in a semiconductor device in order to create truly random, repeatable, and hard to detect cryptographic bits. This may be accomplished by recursively pairing mismatch values of Physically Unclonable Functions (PUF) elements so as to ensure that generated PUF key bits remain insensitive to environmental errors, without affecting the utilization rate of available PUF elements. The pairing process may be applied to any given hardware to generate more stable PUF bit sequences that provide a higher margin of error, increase the number of bits for a given margin of error, or any combination thereof.