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True Random Number Generator Market Size, Share & Trends Analysis Report By Type (Free-Running Oscillator-based TRNG, Noise-based TRNG), By Application, By End Use, By Region, And Segment Forecasts, 2025 - 2030
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Market Size & Trends:

The global true random number generator market size was valued at USD 4.73 billion in 2024 and is projected to grow at a CAGR of 8.2% from 2025 to 2030. The growing threat of quantum computing is pushing demand for advanced random number generators that can ensure stronger cryptographic security. Quantum-based TRNGs are gaining traction for their ability to deliver higher entropy and true unpredictability. This shift is driving innovation in chip-scale solutions that support integration into compact devices across automotive, IoT, and secure communication systems. As cybersecurity requirements intensify, the market for quantum-based TRNGs is expanding steadily with increasing commercial interest.

Companies are collaborating to develop quantum-based TRNG solutions that enhance cryptographic security and address emerging cybersecurity challenges. For instance, in January 2025, Elmos Semiconductor, an electrical company in Germany and ID Quantique signed an MoU to jointly develop a monolithic Quantum Random Number Generator (QRNG) chip measuring just 2mm x 2mm. Combining Elmos' semiconductor expertise with ID Quantique's quantum technology, the ultra-compact QRNG uses in-chip photoemission to ensure top-tier randomness and resistance to cyber threats, supporting applications across automotive, communications, and IoT sectors.

Advances in quantum and photonic TRNG technologies are expanding opportunities across various industries by offering more secure and reliable randomness for cryptographic systems. Unlike traditional methods, these technologies utilize the inherent unpredictability of quantum phenomena to generate true randomness with extremely high entropy. This makes them ideal for applications that require strong encryption, such as digital banking, government communications, and secure IoT networks. As the sophistication of cyberattacks increases-especially with the emergence of quantum computing-industries are rapidly shifting toward these next-generation solutions to future-proof their security infrastructure. Technological progress is also enabling miniaturized, energy-efficient designs that can be embedded in a wide range of devices, from mobile phones to automotive ECUs. Several companies are planning to scale their quantum and photonic TRNG solutions, investing heavily in R&D to lower production costs while maintaining high performance.

Hardware-based TRNGs are preferred for their high entropy and unpredictability, which are essential for strong cryptographic protection. Unlike software-based pseudo-random number generators, hardware TRNGs rely on physical processes that are inherently random, such as thermal noise or quantum effects. This makes them far more resistant to prediction or manipulation, a critical advantage in applications involving encryption, authentication, and secure communications. Their robustness against external factors like electromagnetic interference and voltage fluctuations further enhances their reliability. As cybersecurity demands grow, especially in sectors such as finance, defense, and IoT, hardware TRNGs are being increasingly integrated into chips and security modules. Manufacturers are also focusing on reducing power consumption and size, enabling deployment in compact and mobile systems. These qualities position hardware-based TRNGs as a key component in the evolving landscape of secure digital infrastructure.

Global True Random Number Generator Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global true random number generator market in terms of type, application, end use, and region.

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

Chapter 3. True Random Number Generator Market Variables, Trends & Scope

Chapter 4. True Random Number Generator Market: Type Estimates & Forecasts

Chapter 5. True Random Number Generator Market: Application Estimates & Forecasts

Chapter 6. True Random Number Generator Market: End Use Outlook Estimates & Forecasts

Chapter 7. True Random Number Generator Market: Regional Estimates & Trend Analysis

Chapter 8. Competitive Landscape

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