The reliability and security of telecommunication systems depend on the quality of random number generators (RNGs). Quantum Random Number Generators (QRNGs) enhance randomness over classical methods, improving cryptographic strength. This paper evaluates three QRNG implementations using IBM quantum computers, analyzing their methodologies, performance, and limitations. We introduce a new QRNG algorithm on the IBM Quantum Experience (IBMQ) platform, using real quantum computers instead of simulators, and incorporating post-processing with XOR bit masking. Our algorithm achieves entropy 0.86458 and passes more NIST 800-90B and NIST 800–22 randomness tests, demonstrating its effectiveness and reliability. This research supports secure telecommunication technologies by providing a reliable source of true randomness.
The reliability and security of telecommunication systems depend on the quality of random number generators (RNGs). Quantum Random Number Generators (QRNGs) enhance randomness over classical methods, improving cryptographic strength. This paper evaluates three QRNG implementations using IBM quantum computers, analyzing their methodologies, performance, and limitations. We introduce a new QRNG algorithm on the IBM Quantum Experience (IBMQ) platform, using real quantum computers instead of simulators, and incorporating post-processing with XOR bit masking. Our algorithm achieves entropy 0.86458 and passes more NIST 800-90B and NIST 800–22 randomness tests, demonstrating its effectiveness and reliability. This research supports secure telecommunication technologies by providing a reliable source of true randomness.
Abstract Designing novel circuits and models for generating truly random numbers is of great importance. Recent attention has been focused on the idea of using real quantum computers to generate random numbers. In order to generate purely random bits and numbers, one method relies on the natural superposition of quantum gates. Here, we design a Quantum Random Number Generator (QRNG) exploiting combinations of Hadamard and controlled-Hadamard gates in IBM Quantum Experience (QX). In order to verify that the generated bit sequences were truly random, the proposed circuit’s outputs were subjected to the National Institute of Standards and Technology (NIST) test suite. In comparison to previous works, we found that not only had the total number of passed tests increased, but the P-values had also improved in many cases. For example, in the simulation style of the IBM QX, the number of passed tests is 14 out of 15 standard NIST tests. For the experimental mood of the IBM 16Q Melbourne, the number of passed tests is six without using any extractions. Furthermore, one more test is passed by adding Barrier operations to the circuits, and the P-values have increased. As a result, we found that the proposed method had more passed tests than previous works. The average of P-values for the six passed tests in former research for the mood of using a combination of extractors is about 0.43 . However, the best result we can get with our circuits is around 0.60 (the average of P-values for 14 passed tests), which is an improvement of 0.17 compared to former works . Because of this, our circuits are getting ever closer to being a true QRNG.
Cryptography is the study and practice of secure communication with digital data and focuses on confidentiality, integrity, and authentication. Random number generators (RNGs) generate random numbers to enhance security. Even though the cryptographic algorithms are public and their strength depends on the keys, cryptoanalysis of encrypted ciphers can significantly contribute to the unveiling of the cipher’s key. Therefore, to ensure high data security over a network, researchers need to improve the randomness of keys as they develop cryptosystems. Quantum particles have a leading edge in advancing RNG technology as they can provide true randomness, unlike pseudo-random numbers generators (PRNGs). In order to increase the level of the security of cryptographic systems based on random numbers, this survey focuses on three objectives: Cryptosystems with related cryptographic attacks, RNG-based cryptosystems, and the design of quantum random number generators (QRNGs). This survey aims to provide researchers with information about the importance of RNG-based ciphers and various research techniques for QRNGs that can incorporate quantum-based true randomness in cryptosystems.
Defense, finance, navigation and global internet constellations are now dependent on satellite communication. Nevertheless, the majority of systems continue to use classical pseudo-random number generators (PRNGs) to encrypt and authenticate, and these are susceptible to prediction, replay and side-channel attacks. This paper presents a design of a model to incorporate Quantum True Random Number Generators (QTRNGs) to tap into natural randomness of quantum phenomena into satellite communication systems. The design is a gate based QRNG design based on Hadamard, SX and Pauli-Z gates, which are implemented and tested with NIST 800-22 and NIST 800-90B tests. The protocol architecture uses QRNGs to generate secure keys in ground-to-satellite and inter-satellite links. It shows a better result in entropy, unpredictability and attack resistance. The suggested architecture illustrates the ability of satellites enabled by QRNG to ensure the real-time and futureproof security of the worldwide communication networks.
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
Truly random integers, which are the absolute requirement for this type of cryptography, are necessary for data security. Conventional PRNGs is deterministically which makes them predicted. This type of weakness is present in them. Unlike conventional algorithms, QRNG uses something very fundamental, quantum physics. It has allowed for a breakthrough in using random numbers that are unpredictable. The main goal of the project to design a system including the QRNG (quantum random number generator) and cloud platform developed by IBM. The system produces robust and ideal output for cryptography while being both effective and efficient. We will conduct detailed and effective tuning and testing so as to increase output. Outputs of this project are a QRNG system built on the cloud that can be connected with cryptographic applications, certified sequence, and informational materials of the organization. With this research of QRNGs synchronized with the IBM cloud platform, we make cryptographic security stronger by using the quantum mechanical method to create truly random numbers. Moreover, QRNGs contribute to the cryptographic applications which are intended to be incredibly secure and of high dependability by providing random numbers to enter the realm of crypto-with very little human participation. Basically, the cloud-based architecture enable systems to scale and possible failure resilience via migrating the workload or storing the data online. Quantum improvements will speed up the process of replacing the currently accepted cryptographic paradigm with something opening new ways of digital communication. This research is about quantum physics, cloud computing, and cryptography, bringing together how these concepts operate, as a result, of the unexpected and secure cryptographic applications.
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.