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International Conference Mixed Design of Integrated Circuits and Systems

A Method for Implementing a SHA256 Hardware Accelerator Inside an Quantum True Random Number Generator (QTRNG)

Kamil Witek, M. Caccia, W. Kucewicz, Mateusz Baszczyk, P. Dorosz, Lukasz Mik

Published Jun 29, 2023• 3 citations
Publisher

Abstract

Availability of streams of random numbers is critical in a number of significant applications. e.g. computer security and cryptography, privacy preservation procedures,$\mathbf{IoT}$secure communication, numerical simulation of complex phenomena, gaming and gambling. Hardware generation of random numbers, especially when based on quantum phenomena, is made unbreakable by the same laws of nature. Random Power [1] [2] is focusing on the development of a Quantum-True Random Number generation (QTRNG) platform, producing unpredictable bit streams analyzing the time series of self-amplified endogenous pulses due to stochastically generated charge carriers in a dedicated silicon device. As per NIST recommendations [3], a SHA256 conditioning function was used in order to reduce potential biases and guarantee the required level of entropy. This paper reports the firmware development and implementation of a real-time SHA256 accelerator, which is capable of generating bits in bursts at a maximum rate of 330 Mbps.

DOI
10.23919/mixdes58562.2023.10203268

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Availability of streams of random numbers is critical in a number of significant applications. e.g. computer security and cryptography, privacy preservation procedures,IoT\mathbf{IoT}IoTsecure communication, numerical simulation of complex phenomena, gaming and gambling. Hardware generation of random numbers, especially when based on quantum phenomena, is made unbreakable by the same laws of nature. Random Power [1] [2] is focusing on the development of a Quantum-True Random Number generation (QTRNG) platform, producing unpredictable bit streams analyzing the time series of self-amplified endogenous pulses due to stochastically generated charge carriers in a dedicated silicon device. As per NIST recommendations [3], a SHA256 conditioning function was used in order to reduce potential biases and guarantee the required level of entropy. This paper reports the firmware development and implementation of a real-time SHA256 accelerator, which is capable of generating bits in bursts at a maximum rate of 330 Mbps.
Generating random bit streams is required in various applications, most notably in cyber-security, which is essential for Internet of Everything applications to enable secure communication between interconnected devices. Ensuring high-quality and robust randomness is crucial to mitigate risks associated with predictability and system compromise. True random numbers provide the highest levels of unpredictability. However, known systematic biases that can emerge from physical imperfections, environmental variations, and device aging in the processes exploited for random number generation must be carefully monitored. This article reports the implementation and characterization of an online procedure for the detection of anomalies in a true random bit stream. It is based on the NIST adaptive proportion and repetition count tests, complemented by statistical analysis relying on the Monobit and RUNS tests. The procedure is implemented in firmware through dedicated hardware accelerators processing configurable-length sequences, with automated anomaly detection triggering alerts after three consecutive threshold violations. The implementation is performed simultaneously with bit stream generation and also provides an estimate of the entropy of the source. A statistical analysis of the results from the NIST procedure to evaluate the symbols of the bit-stream as independently and identically distributed is also performed, leading to a computation of the minimum entropy of the source that cross-checks the previously mentioned estimate. The experimental validation of the approach is performed up the bit streams generated by a quantum, silicon-based entropy source.
We propose to develop quantum true random number generation (QTRNG) in IBM's quantum laboratory by implementing the Random Quantum Fourier Transform (RQFT) technique utilizing quantum gates. This approach overcomes the imperfections caused by noise and decoherence in quantum circuits by utilizing the quantum Fourier transform (QFT) to replace the computational basis with a Fourier basis comprising a complex superposition of qubit states. For usage in symmetric and asymmetric cryptographic applications, the RQFT-based QTRNG produces unpredictable high quality random numbers. It satisfies all the preliminary tests, Autocorrelation test, and extensive National Institute of Standards and Technology (NIST) test suites, such as SP 800-90 and SP 800-22 are used to assess the generated sequences randomness in order to guarantee their robustness and reliability.
Random numbers are the lifeline of any cryptographic operation in modern computing. Quantum True Random Number Generator (QTRNG) can yield real random data to replace random-looking periodic sequences. Here, we present the fastest QTRNG on factual Quantum Computational Devices (QCD) locally on our device to save time. To construct a random number generator, the IBM Q Experience called Qiskit is used. The ease of our source Hadamard gate pooled with its verifiably sole randomness is imperative for attaining quantum random number generators at no cost. The inner matrix product of the square of the Hadamard gate is proved to be identified in the quantum lab. Applying the H gate twice on the quantum register cancelled out the H gate pair. It acted as a single Hadamard gate that was practically visualised using the IMB Q experience. The 24-qubit random number is experimented with and investigated in this work. The min-entropy of such generated random numbers is 0.0007244 with the worst-case entropy value of 0.999507. Besides, subsequent verification of genuine randomness was confirmed by steering restart experimentation, & the statistical properties of TRNG were evaluated over autocorrelation study, National Institute of Standards and Technology (NIST) SP 800-90B & 800-22 tests.
True randomness is a basic necessity of secure cryptography. This secures the reliability of encryption keys, digital signatures and authentication mechanisms. Classical random number generators based on deterministic algorithms can introduce patterns and decrease reliability. This paper introduces a Quantum True Random Number Generator (QTRNG) takes advantage of the intrinsic unpredictability of quantum mechanics. The proposed quantum circuit usesRY(π/2)R Y(\pi / 2)RY(π/2)andRZ(π/2)R Z(\pi / 2)RZ(π/2)rotations to create superposition states like Hadamard operation. These gates control the phase and orientation of qubits on the Bloch sphere yields measurement outcomes are inherently random. The resulting distributions are unbiased and balanced offers a source of true randomness. The quality of the generated bitstrings is verified using statistical tests such as the NIST SP 800-22, SP 800-90 test suites and autocorrelation tests. The measurements show high entropy, uniform distribution and low bias satisfy the basic requirements for cryptographic security. Phase-based quantum operations provide an efficient for producing high-quality quantum randomness facilitates the construction of effective quantum-secure cryptographic systems.
Generating random bit streams is required in various applications, most notably cyber-security. Ensuring high-quality and robust randomness is crucial to mitigate risks asso-ciated with predictability and system compromise. True random numbers provide the highest unpredictability levels. However, potential biases in the processes exploited for the random number generation must be carefully monitored. This paper reports the implementation and characterization of an on-line procedure for the detection of anomalies in a true random bit stream. It is based on the NIST Adaptive Proportion and Repetition Count tests, complemented by statistical analysis relying on the Monobit and RUNS. The procedure is firmware implemented and performed simultaneously with the bit stream generation, and providing as well an estimate of the entropy of the source. The experimental validation of the approach is performed upon the bit streams generated by a quantum, silicon-based entropy source.
Random number generators (RNG) are essential elements in many cryptographic systems. True random number generators (TRNG) rely upon sources of randomness from natural processes such as those arising from quantum mechanics phenomena. We demonstrate that a quantum computer can serve as a high-quality, weakly random source for a generalized user-defined probability mass function (PMF). Specifically, QC measurement implements the process of variate sampling according to a user-specified PMF resulting in a word comprised of electronic bits that can then be processed by an extractor function to address inaccuracies due to non-ideal quantum gate operations and other system biases. We introduce an automated and flexible method for implementing a TRNG as a programmed quantum circuit that executes on commercially-available, gate-model quantum computers. The user specifies the desired word size as the number of qubits and a definition of the desired PMF. Based upon the user specification of the PMF, our compilation tool automatically synthesizes the desired TRNG as a structural OpenQASM file containing native gate operations that are optimized to reduce the circuit’s quantum depth. The resulting TRNG provides multiple bits of randomness for each execution/measurement cycle; thus, the number of random bits produced in each execution is limited only by the size of the QC. We provide experimental results to illustrate the viability of this approach.