A post-processing method for true random number generators based on hyperchaos with applications in audio-based generators

Teh, Je Sen; Teng, WeiJian; Samsudin, Azman; Chen, Jiageng

doi:10.1007/s11704-019-9120-2

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…The random number generator (RNG) is indispensable in cryptography technique systems to safeguard information confidentiality because the key being generated by RNG is a sequence of random numbers [1]. RNG is divided into two categories: (1) pseudo-random number generators (PRNG) and ( 2) true random number generators (TRNG) [2].…”

Section: Introductionmentioning

confidence: 99%

Implement quantum random number generation on the IBM quantum computer platform

Nhu Quynh,

Van Anh

2024

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Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standard

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Section: Introductionmentioning

confidence: 99%

Implement quantum random number generation on the IBM quantum computer platform

Nhu Quynh,

Van Anh

2024

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“…Therefore, it can be widely used in various GNU/Linux systems. A post-processing function based on XOR and fair coin operations is implemented [22][23][24][25] to ensure that the final output is unbiased and robust.…”

Section: Introductionmentioning

confidence: 99%

LETRNG—A Lightweight and Efficient True Random Number Generator for GNU/Linux Systems

Chen

Zhu

Tian

et al. 2023

Tsinghua Sci. Technol.

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Unpredictable and irreproducible digital keys are required to modulate security-related information in secure communication systems. True random number generators (TRNGs) rather than pseudorandom number generators (PRNGs) are required for the highest level of security. TRNG is a significant component in the digital security realm for extracting unpredictable binary bitstreams. Presently, most TRNGs extract high-quality "noise" from unpredictable physical random phenomena. Thus, these applications must be equipped with external hardware for collecting entropy and converting them into a random digital sequence. This study introduces a lightweight and efficient true random number generator (LETRNG) that uses the inherent randomness of a central processing unit (CPU) and an operating system (OS) as the source of entropy. We then utilize a lightweight post-processing method based on XOR and fair coin operation to generate an unbiased random binary sequence. Evaluations based on two famous test suites (NIST and ENT) show that LETRNG is perfectly capable of generating high-quality random numbers suitable for various GNU/Linux systems.

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