Raw QPP-RNG randomness via system jitter across platforms: a NIST SP 800-90B evaluation
High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG , a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven me...
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| Published in | Scientific reports Vol. 15; no. 1; pp. 27718 - 19 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
29.07.2025
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2045-2322 2045-2322 |
| DOI | 10.1038/s41598-025-13135-8 |
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| Abstract | High-quality randomness is fundamental to the security of modern cryptographic systems. We present
QPP-RNG
, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG’s core mechanism measures the elapsed time of randomized array sorting operations–where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters–and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between
and
bits/byte. It passed all NIST SP 800-90B IID tests with
-values significantly above the
threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint–and consequently the generated randomness–exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG’s entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique’s Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat’s CPU Time Jitter RNG (7.4528 bits/byte) and Quside’s PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip’s ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. |
|---|---|
| AbstractList | High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters-including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG's core mechanism measures the elapsed time of randomized array sorting operations-where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters-and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between [Formula: see text] and [Formula: see text] bits/byte. It passed all NIST SP 800-90B IID tests with [Formula: see text]-values significantly above the [Formula: see text] threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint-and consequently the generated randomness-exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG's entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique's Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat's CPU Time Jitter RNG (7.4528 bits/byte) and Quside's PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip's ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG , a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG’s core mechanism measures the elapsed time of randomized array sorting operations–where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters–and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between and bits/byte. It passed all NIST SP 800-90B IID tests with -values significantly above the threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint–and consequently the generated randomness–exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG’s entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique’s Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat’s CPU Time Jitter RNG (7.4528 bits/byte) and Quside’s PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip’s ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG’s core mechanism measures the elapsed time of randomized array sorting operations–where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters–and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between $$7.85$$ and $$7.95$$ bits/byte. It passed all NIST SP 800-90B IID tests with $$p$$ -values significantly above the $$\alpha =0.01$$ threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint–and consequently the generated randomness–exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG’s entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique’s Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat’s CPU Time Jitter RNG (7.4528 bits/byte) and Quside’s PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip’s ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. Abstract High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG’s core mechanism measures the elapsed time of randomized array sorting operations–where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters–and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between $$7.85$$ and $$7.95$$ bits/byte. It passed all NIST SP 800-90B IID tests with $$p$$ -values significantly above the $$\alpha =0.01$$ threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint–and consequently the generated randomness–exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG’s entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique’s Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat’s CPU Time Jitter RNG (7.4528 bits/byte) and Quside’s PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip’s ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters–including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG’s core mechanism measures the elapsed time of randomized array sorting operations–where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters–and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between and bits/byte. It passed all NIST SP 800-90B IID tests with -values significantly above the threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint–and consequently the generated randomness–exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG’s entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique’s Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat’s CPU Time Jitter RNG (7.4528 bits/byte) and Quside’s PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip’s ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters-including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG's core mechanism measures the elapsed time of randomized array sorting operations-where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters-and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between [Formula: see text] and [Formula: see text] bits/byte. It passed all NIST SP 800-90B IID tests with [Formula: see text]-values significantly above the [Formula: see text] threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint-and consequently the generated randomness-exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG's entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique's Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat's CPU Time Jitter RNG (7.4528 bits/byte) and Quside's PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip's ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount.High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests entropy from diverse system-level jitters-including CPU pipeline timing divergences, DRAM refresh cycle perturbations, cache miss-driven memory access latencies, and other subtle hardware and operating system-induced fluctuations. QPP-RNG's core mechanism measures the elapsed time of randomized array sorting operations-where each Fisher-Yates shuffle is infinitesimally perturbed by these microscopic jitters-and amplifies these timing variations into cryptographically strong randomness through a quantum permutation pad (QPP) architecture, all achievable on commodity hardware. The raw output of QPP-RNG underwent rigorous evaluation for independent and identically distributed (IID) behavior using the NIST SP 800-90B IID test suite, alongside the comprehensive NIST SP 800-22 and ENT statistical test batteries. Across a range of platforms, including Windows, macOS, and Raspberry Pi, QPP-RNG consistently achieved high IID min-entropy between [Formula: see text] and [Formula: see text] bits/byte. It passed all NIST SP 800-90B IID tests with [Formula: see text]-values significantly above the [Formula: see text] threshold, confirming that its generated randomness is statistically indistinguishable from ideal IID sources derived directly from system jitter. Cross-platform analyses spanning x86_64 and ARM64 architectures further demonstrate that the extracted jitter fingerprint-and consequently the generated randomness-exhibits remarkable statistical consistency, irrespective of the underlying hardware or operating system. QPP-RNG's entropy density compares favorably with leading commercial entropy sources. It matches or slightly exceeds the NIST IID-certified min-entropy of ID Quantique's Quantis QRNG (7.8744 bits/byte), and significantly outperforms both Red Hat's CPU Time Jitter RNG (7.4528 bits/byte) and Quside's PCIe One quantum entropy source (6.5136 bits/byte). Even against specialized hardware RNGs like Microchip's ECC608 (4.0568 bits/byte), QPP-RNG demonstrates superior performance using only general-purpose processors. By effectively transforming otherwise discarded system noise into a reliable and high-quality entropy stream, QPP-RNG establishes a novel paradigm for embedded security, providing a robust entropy source on general-purpose devices without specialized hardware. This makes it especially well-suited for resource-constrained Internet of Things (IoT) and edge computing applications where strong entropy sources are paramount. |
| ArticleNumber | 27718 |
| Author | Kuang, Randy Vrana, Georgia Lou, Dafu |
| Author_xml | – sequence: 1 givenname: Georgia surname: Vrana fullname: Vrana, Georgia organization: Quantropi (Canada) – sequence: 2 givenname: Dafu surname: Lou fullname: Lou, Dafu organization: Quantropi (Canada) – sequence: 3 givenname: Randy surname: Kuang fullname: Kuang, Randy email: randy.kuang@quantropi.com organization: Quantropi (Canada) |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40730632$$D View this record in MEDLINE/PubMed |
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| Keywords | Quantum permutation pad System jitter Statistical testing Pseudo-random number generator PQC Random number generator IID randomness RNG Platform-independent randomness Cryptographic primitives QPP TRNG Post-quantum cryptography Uniform distribution Entropy source CPU time jitter Permutation test True random number generator Permutation entropy NIST SP800-90B PRNG |
| Language | English |
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| Snippet | High-quality randomness is fundamental to the security of modern cryptographic systems. We present
QPP-RNG
, a true random number generator (TRNG) that... High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG , a true random number generator (TRNG) that... High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that harvests... Abstract High-quality randomness is fundamental to the security of modern cryptographic systems. We present QPP-RNG, a true random number generator (TRNG) that... |
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| SubjectTerms | 639/301 639/705 Algorithms Cryptography Entropy Humanities and Social Sciences Integrated circuits Internet of Things Linux multidisciplinary PRNG Pseudo-random number generator QPP Quantum computing Quantum permutation pad Random number generator RNG Science Science (multidisciplinary) Software Statistics |
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| Title | Raw QPP-RNG randomness via system jitter across platforms: a NIST SP 800-90B evaluation |
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