TRNG Circuit with Ring and Metastable Oscillators for High Entropy

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Solution Overview

Problem

Current true random number generators (TRNGs) face challenges in providing secure and improved entropy between generated sequences, often resulting in random number sequences that are either too long, wasting memory, or not meeting the required length, and lack robustness and efficiency.

Innovation Solution

The proposed solution involves an apparatus and method using a combination of ring oscillators and metastable oscillators with adjustable frequencies, encoded and scrambled random data generation, and XOR logic circuits to produce high-entropy random numbers, optimized for secure storage and efficient memory usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the random number sequence length is increased to ensure uniqueness, then the security and uniqueness of random data is improved, but the memory space occupied increases, wasting computer memory

Engineering Contradiction:
Improveuniqueness of random number sequenceVSAvoidmemory space occupied
Core Design Contradiction:
ReliabilityVSVolume of stationary object

Solution Approach 1:

The patent extracts only the necessary portion of random data (e.g., 8 bits) from a longer generated sequence, storing only the essential unique identifier while discarding redundant portions. This reduces memory occupation while maintaining the uniqueness guarantee.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system dynamically adjusts the effective length of stored random sequences based on application requirements. Instead of always storing maximum length sequences, it adapts the storage size to the actual need, optimizing memory usage while ensuring sufficient uniqueness.

Inventive Principle:
Principle #15Dynamics

2Volume of stationary object

If the random number sequence length is reduced to save memory, then memory usage is optimized, but the uniqueness and security of random data may be compromised

Engineering Contradiction:
Improvememory space occupiedVSAvoiduniqueness of random number sequence
Core Design Contradiction:
Volume of stationary objectVSReliability

Solution Approach 1:

The patent changes the parameter of sequence length from a fixed large value to a dynamically determined optimal value. By analyzing the relationship between sequence length and uniqueness probability, it identifies the minimum sufficient length (e.g., 8 bits providing 256 unique values) that satisfies security requirements while minimizing memory usage.

Inventive Principle:
Principle #35Parameter changes

3Device complexity

If traditional TRNG designs are used, then implementation is simple, but entropy security between generated sequences is insufficient

Engineering Contradiction:
Improvestructure complexityVSAvoidentropy security
Core Design Contradiction:
Device complexityVSReliability

Solution Approach 1:

The patent merges multiple independent TRNG modules (e.g., first and second TRNGs generating different bit sequences) and combines their outputs through XOR operations. This combination increases the overall entropy and security between generated sequences while maintaining relatively simple individual module structures.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The system uses composite random data generation by combining outputs from different TRNG sources with different entropy characteristics. This creates a composite random sequence with enhanced security properties, analogous to using composite materials to achieve superior performance.

Inventive Principle:
Principle #40Composite materials

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach results in a reliable, efficient, and secure true random number generator with improved entropy, capable of producing random sequences that meet high entropy standards (>0.97) and pass NIST criteria, while optimizing memory usage and security.

Implementation Method 1

Such devices are often based on microscopic phenomena that generate low-level, statistically random 'noise' signals, such as thermal noise

Methodology Applied
Scientific EffectThermal noise:

Implementation Method 2

a) Ring Oscillator (RO TRNG); or a b) Metastability (META TRNG)

Methodology Applied
Scientific EffectMetastability: Metastability

Data Source

PatentUS20230161560A1Apparatus for generating random data and a method thereof
Publication Date: 2023.05.25 L&T SEMICONDUCTOR TECHNOLOGIES LTD
  • US20230161560A1 patent drawing
  • US20230161560A1 patent drawing
  • US20230161560A1 patent drawing

AI summary

The present disclosure pertains to a circuitry for generating random data. The random data can be numbers. The circuitry includes a ring oscillator, a metastable oscillator, a first circuitry, and an analogue circuitry. The ring oscillator has a ring oscillator output frequency selectable through a selectable input of the ring oscillator. The metastable oscillator has a metastable oscillator output frequency selectable through a selectable input of the metastable oscillator. The first circuitry has a ring oscillator chain size selection logic circuit. The analogue circuitry has a capacitor and a switch used for varying frequency of the ring oscillator. The switch is configured to be controlled by the selection logic circuit of the first circuitry.