Random Number Quality Indication Logic Circuit
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Solution Overview
Problem
Random number generators in various applications face challenges in achieving sufficient entropy, leading to issues with the quality of generated numbers, particularly in identifying instances of repetitive or insufficiently different numbers, which can compromise security and reliability in data exchange applications.
Innovation Solution
A system that includes a logic circuit and memory to determine the relationship between previous and current randomly generated numbers, generating an indication of quality, and an output conditioner that filters or corrects the output based on entropy thresholds, ensuring that only numbers meeting the required entropy standards are provided.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a random number generator is used to generate numbers for security applications, then data exchange can be performed, but the generated numbers may have insufficient entropy and repetitive patterns that compromise security
Solution Approach 1:
The patent introduces an intermediary quality assessment system between the random number generator and the security application. This system includes logic circuits that calculate string distances between consecutive random numbers and generate quality indications, acting as a mediator to filter out low-quality numbers before they reach the security application, thus resolving the contradiction between maintaining security reliability and ensuring entropy quality
Solution Approach 2:
The patent implements feedback mechanisms where the quality indication of generated random numbers is fed back to the system. The logic circuit continuously monitors the entropy quality by comparing consecutive numbers and provides feedback signals that indicate whether the random number generator is producing sufficient entropy, allowing for real-time quality control in security-critical applications
2Productivity
If the random number generator outputs all generated numbers, then productivity is high, but low-quality numbers with insufficient entropy are also included
Solution Approach 1:
The patent applies preliminary action by performing quality assessment on random numbers immediately after generation but before they are output or used. The logic circuit calculates string distances and generates quality indications in real-time, filtering out low-quality numbers proactively before they can compromise security applications, thus maintaining both high productivity and quality standards
Solution Approach 2:
The patent applies local quality control by assessing the entropy quality of individual random numbers or small batches independently. The quality indication is generated locally for each random number based on its string distance from previous numbers, allowing selective filtering of low-quality outputs while maintaining overall high productivity of the random number generator
3Manufacturing precision
If quality assessment logic is added to evaluate random number entropy, then entropy quality improves, but device complexity increases
Solution Approach 1:
The patent replaces complex statistical entropy analysis with a simpler mechanical-like operation: calculating string distance between consecutive random numbers. This substitution uses basic comparison logic instead of sophisticated entropy measurement algorithms, significantly reducing device complexity while still providing effective quality assessment for detecting repetitive patterns
Solution Approach 2:
The patent changes the assessment parameter from complex entropy measurement to simple string distance calculation. By measuring the difference between consecutive random numbers using straightforward comparison logic, the system achieves practical entropy quality control without requiring complex computational resources or sophisticated algorithms
Data Source
AI summary
One or more examples relate to generation of quality indications for a randomly generated number or a random number generator more generally. An example apparatus may include a memory and a logic circuit. Such a memory is to receive and store a previous randomly generated number and a current randomly generated number. Such a logic circuit is to: determine a relationship between the previous randomly generated number and the current randomly generated number; and generate an indication of quality of the current randomly generated number at least partially responsive to the determined relationship between the previous randomly generated number and the current randomly generated number.