True Random Number Generator Using Image Least Significant Bits

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Solution Overview

Problem

Existing portable random number generators face challenges in generating unbiased, non-predictable, and robust random sequences due to environmental dependencies and complexity, particularly in physical systems, and often require cumbersome processes like digitizing chaotic sources which are slow and limited in portability.

Innovation Solution

A method utilizing the microstructure and noise found in digital images, specifically extracting the least significant bits from digitized images using widely available off-the-shelf hardware like smartphones and cameras, which can handle both raw and lossy compressed images, to generate true random bits, thus eliminating the need for subsequent processing and environmental constraints.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If physical systems are used for random number generation, then robustness and quality of random sequences are improved, but device complexity and portability deteriorate

Engineering Contradiction:

Improvequality of random sequencesVSAvoiddevice complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces complex physical random number generation systems with a computational approach that extracts randomness from digital image data. Instead of using physical devices like radioactive decay sources or electronic noise generators, the invention uses software-based processing of image least significant bits to generate random sequences, thereby eliminating the need for complex physical hardware while maintaining randomness quality.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If physical systems are used for random number generation, then robustness and quality of random sequences are improved, but portability deteriorates

Engineering Contradiction:

Improvequality of random sequencesVSAvoidportability

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent replaces physical random number generation systems with a computational method that can run on any device capable of storing and processing digital images. By substituting physical hardware with software-based image processing, the invention achieves portability across smartphones, computers, and other digital devices while maintaining the quality of random sequence generation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If digitized images from chaotic sources are used, then random seed generation is achieved, but the process is slow and cumbersome

Engineering Contradiction:

Improverandom seed generationVSAvoidspeed of generation

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent extracts only the least significant bits from digital image data to generate random sequences, rather than processing entire images or using complex chaotic source digitization. This extraction approach focuses on the most random portions of image data (the least significant bits that contain noise and microstructure), significantly reducing processing time and improving generation speed while maintaining randomness quality.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent uses only a partial portion of the image data (specifically the least significant bits) rather than processing complete images. This partial action approach generates sufficient random entropy from a small fraction of the total image information, dramatically improving processing speed and productivity compared to comprehensive image analysis methods.

Inventive Principle:

Principle #16Partial or excessive action

4Quantity of substance

If all bits in pixel data are used for random generation, then more random data is obtained, but bias and predictability increase

Engineering Contradiction:

Improveamount of random dataVSAvoidunbiased and non-predictable sequences

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The patent extracts only the least significant bits from pixel data, discarding the more significant bits that contain structured information. This selective extraction isolates the random noise components while eliminating predictable patterns, achieving both sufficient quantity of random data and high reliability of unbiased sequences.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments pixel data into different bit significance groups and uses only the least significant portion for random number generation. This segmentation separates the random noise elements (LSBs) from the structured visual information (MSBs), allowing extraction of pure randomness while maintaining adequate data quantity for practical applications.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS8379848B2Method of providing a portable true random number generator based on the microstructure and noise found in digital images

Publication Date: 2013.02.19 CAPE LIGHT INST

AI summary

A method of providing a portable true random number generator based on the microstructure and noise found in digital images is claimed and disclosed. Using the lowest significant bits of digitized images, strings of binary data are extracted. These raw strings are shown to pass the DIEHARD, NIST, and ENT tests for randomness for a robust selection of natural images. This information is available to, and may be processed by off-the-shelf technology including smartphones or other embedded devices without undue constraints on physical and environmental parameters. The method represents a significantly improved portable means of random number generation for all security, cryptographic, entertainment and PSI applications.