Strong PUF Challenge Obfuscation Using Rubik's Cube Matrices
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Solution Overview
Problem
Current strong PUFs are vulnerable to machine learning attacks, and existing methods to enhance resistance either compromise stability due to noise amplification or have limited complexity in challenge-response mapping, making them susceptible to higher-order attacks.
Innovation Solution
A method involving cryptographic challenge generation using Rubik's cube matrix transformations and matrix multiplication to obfuscate challenges, ensuring stability and complexity in the mapping relationship, where subsequent obfuscations reuse previous cryptographic matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If response obfuscation is used to resist machine learning attacks, then machine learning attack resistance is improved, but PUF stability deteriorates due to noise amplification
Solution Approach 1:
The patent segments the PUF response into multiple independent PUFs (first PUF, second PUF, etc.), each generating a partial response. The final response is constructed by combining these partial responses through a selection mechanism that does not require obfuscation of individual PUF responses, thereby avoiding noise amplification while maintaining security.
Solution Approach 2:
The patent introduces a third party (server or trusted component) as an intermediary that collects responses from multiple PUFs and constructs the final response. This intermediary approach allows the system to aggregate information from multiple sources without requiring obfuscation, thus avoiding the noise amplification problem while achieving machine learning attack resistance.
2Reliability
If challenge obfuscation is used to resist machine learning attacks, then machine learning attack resistance is improved, but the mapping relationship complexity is limited
Solution Approach 1:
The patent segments the challenge-response mapping into multiple independent PUFs, each with its own challenge-response pairs. The final mapping relationship is constructed by combining these segmented mappings through a selection mechanism, achieving high complexity without requiring complex obfuscation algorithms.
Solution Approach 2:
The patent transitions from a single-dimensional challenge-response mapping to a multi-dimensional approach by using multiple PUFs in parallel. Each PUF provides an independent mapping dimension, and the final response is constructed by selecting from these dimensions, thereby increasing mapping complexity without requiring complex obfuscation.
Data Source
AI summary
A method for improving ability of strong PUF to resist machine learning attacks. When obfuscating challenge, method comprises: performing conversion on Rubik's cube matrix on basis of current challenge to generate cryptographic matrix, and constructing challenge matrix based on current challenge; determining matrix multiplication pattern of cryptographic matrix and challenge matrix on basis of cryptographic matrix, multiplying cryptographic matrix by challenge matrix to obtain obfuscation matrix, converting elements in obfuscation matrix to 0 or 1 according to parity of elements to obtain cryptographic challenge matrix; extracting elements in cryptographic challenge matrix to form cryptographic challenge, if PUF response generated currently is first PUF response of PUF response sequence, Rubik's cube matrix that generates cryptographic challenge in current obfuscation is randomly generated; if not, Rubik's cube matrix that generates cryptographic challenge in current obfuscation is cryptographic matrix generated by previous obfuscation.