Adaptive Hamming Threshold for PUF String Matching
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Solution Overview
Problem
Existing methods for assigning fixed identifiers to fuzzy identifiers in Physical Unclonable Functions (PUFs) rely on reliable matching, which can lead to high false acceptance and rejection rates due to varying characteristics among PUF devices.
Innovation Solution
An improved identification method that adapts the matching threshold based on the characteristics of the PUF device, using a threshold setting function to determine a specific matching threshold for each enrollment PUF string, thereby reducing false acceptance and rejection rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed matching threshold is used for all PUF string comparisons, then the matching process is simple and fast, but the false acceptance rate and false rejection rate increase due to varying characteristics among PUF devices
Solution Approach 1:
The patent applies dynamics by making the matching threshold adjustable rather than fixed. The threshold is dynamically adapted based on the characteristics of each PUF device, allowing the system to optimize identification accuracy for each device while maintaining a relatively simple matching process. This resolves the contradiction by enabling the threshold to change according to device-specific parameters.
Solution Approach 2:
The patent changes the parameter of the matching threshold from a fixed value to a variable that depends on PUF device characteristics. By adjusting the threshold parameter based on measured characteristics such as bit error rates or Hamming distances, the system improves identification reliability without requiring completely complex matching procedures.
2Adaptability or versatility
If a single matching threshold is applied to all PUF devices, then the system is easy to operate, but it cannot adapt to the varying characteristics of different PUF devices
Solution Approach 1:
The patent applies preliminary action by measuring and characterizing each PUF device before using it for identification. The system performs initial measurements to determine device-specific characteristics and sets appropriate thresholds in advance, so that during actual operation the matching process remains simple while being adapted to each device's characteristics.
Solution Approach 2:
The system changes the matching threshold parameter based on measured PUF characteristics. By adjusting this key parameter according to device-specific properties such as bit error rates or response stability, the system achieves adaptability without complicating the operational interface or user interaction.
3Measurement precision
If the matching threshold is optimized for each PUF device, then false acceptance and rejection rates are reduced, but the threshold determination process becomes more complex
Solution Approach 1:
The patent applies self-service by enabling each PUF device to effectively determine its own optimal matching threshold through measurement of its characteristics. The system automatically analyzes device-specific parameters and sets appropriate thresholds without requiring external intervention or complex manual configuration, thus improving precision while keeping the process relatively simple.
Solution Approach 2:
The system uses feedback from measurements of PUF device characteristics to adjust the matching threshold. By continuously monitoring device performance and adapting the threshold based on observed behavior, the system improves matching precision while using straightforward feedback mechanisms rather than complex algorithms.
Data Source
AI summary
Some embodiments are directed to matching a received PUF string. For example, a matching enrollment PUF string may be found by searching for a matching enrollment PUF string in a database. The searching may include iteratively determining if a Hamming distance between the received PUF string and an enrollment PUF string retrieved from the database is below a threshold at least until a matching enrollment PUF string is found. The threshold depends on the specific retrieved enrollment PUF string and/or the received PUF string.