FBB-Biased Ring Oscillator TRNG for Higher Thermal Noise Entropy

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Solution Overview

Problem

Current True Random Number Generators (TRNGs) face challenges in meeting the increasing demands of cryptography, particularly in lightweight cryptography for IoT and the emergence of quantum computing, due to limitations in entropy generation and noise sources, which affect the unpredictability and security of cryptographic primitives.

Innovation Solution

A TRNG design utilizing Fully Depleted Silicon-On-Insulator (FD-SOI) transistors with Low Voltage Threshold (LVT) and Forward Body Biasing (FBB) to reduce scintillation noise, enhancing the calculation of thermal noise entropy, and a circuit to detect the maximum thermal noise contribution, optimizing the number of oscillations for improved entropy quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If multiple ring oscillators are used in parallel to meet entropy standards, then the entropy generation quality improves, but the power consumption and device complexity increase

Engineering Contradiction:
Improveentropy generation qualityVSAvoidpower consumption
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent changes the electrical parameters of the transistor by applying forward body bias (FBB) to reduce the threshold voltage. This parameter modification allows the ring oscillator to operate with optimized noise characteristics, achieving high entropy quality with a single oscillator instead of requiring multiple parallel oscillators, thereby reducing power consumption and device complexity

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent dynamically adjusts the body bias voltage to optimize the transistor operation point. By dynamically controlling the threshold voltage through FBB, the system can maximize thermal noise contribution while minimizing scintillation noise, achieving optimal entropy generation quality with reduced hardware requirements

Inventive Principle:
Principle #15Dynamics

2Productivity

If the threshold voltage of transistors is lowered to increase oscillation frequency, then the productivity improves, but the scintillation noise increases reducing entropy quality

Engineering Contradiction:
Improveoscillation frequencyVSAvoidentropy quality
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The patent applies forward body bias to dynamically adjust the threshold voltage parameter. This allows the system to operate at optimal points where the threshold voltage is low enough to maintain high oscillation frequency but not so low that scintillation noise dominates, thus simultaneously achieving high productivity and high entropy quality

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent uses periodic switching between different body bias conditions to optimize the noise characteristics. By periodically adjusting the bias state, the system can maximize thermal noise contribution during specific phases while minimizing scintillation noise, achieving high entropy quality at high oscillation frequencies

Inventive Principle:
Principle #19Periodic action

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 increases the quality of entropy generation, enhancing the security and reliability of TRNGs by maximizing thermal noise contribution while minimizing scintillation and quantization noise, thus addressing the constraints of modern cryptographic requirements.

Implementation Method 1

Thermal noise is perfectly white, i.e. uncorrelated, and therefore contributes to the generation of a perfectly unpredictable random element

Methodology Applied
Scientific EffectThermal noise: Joule Heating

Implementation Method 2

scintillation noise (or 'flicker' noise). Thermal noise is perfectly white, i.e. uncorrelated, and therefore contributes to the generation of a perfectly unpredictable random element. Conversely, scintillation noise is an auto-correlated noise that induces predictability in the jitter

Methodology Applied
Scientific EffectScintillation noise: Scintillation

Implementation Method 3

the source of randomness of the TRNG is the jitter of the RO(s), i.e. the difference between the theoretical period and the actual period of the output signal of the or each RO

Methodology Applied
Scientific EffectJitter:

Data Source

PatentEP4280094A1Fbb-biased lvd dual-gate transistor random number generator
Publication Date: 2023.11.22 COMMISSARIAT A LENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
  • EP4280094A1 patent drawingFigure 1~3
  • EP4280094A1 patent drawingFigure 4~5
  • EP4280094A1 patent drawing

AI summary

Random number generator comprising at least one ring oscillator (104) comprising at least one inverter (112.1 - 112.n) formed by at least two FDSOI LVT transistors (116.1, 117.1), one being of type NMOS and the other being of type PMOS, characterized in that it further comprises a circuit (128) for applying voltages to the back gates of the transistors (116.1, 117.1) configured to bias the transistors (116.1, 117.1) in FBB mode.