Random Number Generation Using Material Optical Variability
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Solution Overview
Problem
Current random number generators, especially pseudo-random number generators, are vulnerable to cryptoanalytic attacks due to their deterministic processes, and physical random number generators are often costly and not widely accessible for high-quality random bit generation.
Innovation Solution
The method involves measuring physical variability in material samples, such as optical, acoustical, or structural features, to derive initial random bit streams, which are then processed using randomness extraction algorithms to generate high-quality random numbers, leveraging inherent material properties for cost-effective and secure randomness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pseudo random number generators are used, then cost and accessibility are improved, but security and reliability deteriorate due to deterministic processes being vulnerable to cryptoanalytic attacks
Solution Approach 1:
The patent replaces deterministic mechanical/computational random number generation with a physical system based on optical measurement of material properties. A camera captures optical images of material samples, and randomness extraction algorithms process the pixel intensity variations to generate cryptographically secure random bits, substituting physical measurement for computational prediction.
Solution Approach 2:
The system utilizes the inherent physical variability already present in common materials without requiring additional randomizing components or expensive specialized equipment. The material samples themselves provide the entropy source through their natural optical property variations, making the system self-sufficient and cost-effective.
2Reliability
If physical random number generators are used, then security and reliability are improved, but cost and accessibility worsen due to high implementation costs
Solution Approach 1:
The patent uses inexpensive, readily available material samples as the source of randomness. These common materials with varying optical properties serve as single-use or reusable entropy sources without requiring expensive specialized hardware, making high-quality random number generation accessible and cost-effective.
Solution Approach 2:
The system creates digital copies of physical material properties through optical imaging. Instead of requiring direct physical interaction with complex randomizing devices, the camera captures optical images that replicate the random patterns, which are then processed to extract random bits, providing a cheap digital representation of physical randomness.
3Measurement precision
If inherent physical variability of materials is utilized, then quality and distinctiveness of random bits are improved, but device complexity increases due to measurement and processing requirements
Solution Approach 1:
The patent introduces a camera as an intermediary device that bridges the physical material samples and the digital random bit generation. The camera captures optical images of the materials, converting physical optical property variations into digital pixel data that can be processed by randomness extraction algorithms, simplifying the overall measurement and processing chain.
Solution Approach 2:
The system uses a camera, which is a common multi-functional device, for the specific purpose of capturing optical patterns from material samples. This universal device serves multiple functions including imaging, pattern capture, and data acquisition, reducing the need for specialized equipment and lowering overall system complexity.
Data Source
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AI summary
Systems and methods for generating random bits by using physical variations present in material samples are provided. Initial random bit streams are derived from measured material properties for the material samples. In some cases, secondary random bit streams are generated by applying a randomness extraction algorithm to the derived initial random bit streams.