Quantum Randomness for Next-Generation Security

Why Unpredictable Quantum Entropy is the Bedrock of Quantum-Safe Cryptography

The Unsung Hero of Cybersecurity: Unpredictability

When we think about online security, we naturally picture visible protective steps: entering a complex password, authenticating with a smartphone code, or seeing the green padlock icon in our browser address bar. Yet, beneath every encrypted banking transaction, industrial control system, or confidential communication link lies an invisible, indispensable hero: random numbers.

Random numbers are the secret seeds used to build encryption keys, generate digital signatures, and execute secure protocol handshakes. No matter how strong an encryption algorithm is mathematically, if the random numbers feeding it are predictable, an attacker can guess the encryption keys and unlock the system without ever cracking the algorithm itself.

The Achilles’ Heel of Classical Randomness

Here lies a fundamental problem in conventional computing: standard microprocessors are deterministic machines designed to strictly follow rules, making them incapable of creating true randomness. Instead, conventional software relies on Pseudo-Random Number Generators (PRNGs)—mathematical formulas that calculate sequences of numbers designed to look random.

Because PRNG outputs are calculated from an initial ‘seed’ value, an adversary who discovers the seed or analyzes algorithmic patterns can accurately calculate every future key. Classical physical True Random Number Generators (TRNGs)—which harvest physical noise like thermal jitter—offer improvements, but they can face limitations in speed and stability, and may require careful design to resist environmental influence.

Enter Quantum Randomness (QRNG): Nature’s True Entropy

To achieve randomness rooted in the laws of physics, we turn to quantum mechanics. In classical physics, outcomes are theoretically predictable if all variables are known. In quantum physics, however, nature operates on fundamental probabilities. Physical events such as quantum optical vacuum fluctuations produce outcomes that cannot be pre-determined by any computer or formula.

A Quantum Random Number Generator (QRNG) harnesses these quantum fluctuations to generate true physical entropy. Because the randomness originates from quantum indeterminacy rather than a mathematical algorithm, the underlying source cannot be predicted or reverse-engineered—giving QRNGs a fundamental advantage over algorithm-based approaches.

Fraunhofer IPMS: Pioneering High-Speed Quantum Entropy

At Fraunhofer IPMS, researchers translate these quantum physical principles into high-performance hardware solutions for cybersecurity. By combining photonic technology and advanced microelectronics, Fraunhofer IPMS develops QRNG systems capable of delivering true quantum randomness at multi-gigabit speeds.

• Multi-Gbps Performance: Achieving random bit rates exceeding 4 Gbit/s to meet the demands of modern high-speed data networks, cloud infrastructure, and real-time encryption.
• Rigorous Certification Standards: Validated against international randomness evaluation suites, including BSI AIS 20/31 (high-security physical RNG requirements) and NIST SP 800-22.
• Industrial Integration: Focusing on compact chip-scale miniaturization, FPGA/ASIC IP cores, and flexible ‘Entropy-as-a-Service’ models to enable seamless integration into hardware security modules (HSMs) and industrial edge hardware.

The Q-FENCE Shield: Why We Need Both QRNG and Post-Quantum Cryptography

To understand how European cybersecurity is evolving under the Q-FENCE project, it is essential to see how different quantum technologies work together. A major threat facing modern communications is ‘Store Now, Decrypt Later’ (SNDL)—where hostile actors record encrypted network traffic today, planning to decrypt it in the future using quantum computers running Shor’s algorithm.

SNDL attacks target the mathematical structure of asymmetric public-key exchange algorithms (such as RSA or ECC). Countering SNDL requires Post-Quantum Cryptography (PQC)—new mathematical algorithms resistant to quantum cracking. QRNG does not replace PQC; rather, it provides the essential physical fuel that makes PQC work reliably.

Post-Quantum Cryptography algorithms rely heavily on random seeds to construct quantum-safe keys. If a PQC system relies on a weak or predictable PRNG, attackers can bypass the quantum-safe algorithm entirely by guessing the random seed. While QRNG doesn’t defend against SNDL directly, it ensures that the PQC algorithms doing that job are built on the highest-quality physical entropy available—strengthening the overall quantum defense from the ground up.

Building a Quantum-Resilient Tomorrow

Future-proof cybersecurity requires a complete security stack. As part of the Q-FENCE project, Fraunhofer IPMS is proud to contribute high-speed quantum random number generation technology, ensuring that Europe’s next-generation digital defenses are anchored on a solid foundation of true physical randomness.

➜ Learn more about the Q-FENCE project and Fraunhofer IPMS QRNG solutions.