Generating high-quality random numbers is essential for cryptography, statistical simulations, and cybersecurity. While pseudo-random number generators (PRNGs) are computationally efficient, their deterministic nature introduces potential security vulnerabilities. Recent research has explored chaotic systems as entropy sources due to their sensitivity to initial conditions-a key property for randomness generation. An emerging direction involves leveraging chaos in quantum systems. This paper proposes a quantum-inspired PRNG based on the Quantum Kicked Rotor (QKR), a well-known model in quantum chaos exhibiting complex dynamics such as dynamical localization. The method simulates the QKR and extracts pseudo-random sequences through momentum basis measurements. The generated sequences are evaluated for statistical quality, including the NIST 800-22 standard, which passed all 15 test. The sequences exhibit strong non-periodicity, a critical property for secure cryptographic applications. The proposed approach combines the unpredictability of quantum chaos with the scalability of classical simulation, offering a practical and efficient alternative for secure random number generation.
Generating high-quality random numbers is essential for cryptography, statistical simulations, and cybersecurity. While pseudo-random number generators (PRNGs) are computationally efficient, their deterministic nature introduces potential security vulnerabilities. Recent research has explored chaotic systems as entropy sources due to their sensitivity to initial conditions-a key property for randomness generation. An emerging direction involves leveraging chaos in quantum systems. This paper proposes a quantum-inspired PRNG based on the Quantum Kicked Rotor (QKR), a well-known model in quantum chaos exhibiting complex dynamics such as dynamical localization. The method simulates the QKR and extracts pseudo-random sequences through momentum basis measurements. The generated sequences are evaluated for statistical quality, including the NIST 800-22 standard, which passed all 15 test. The sequences exhibit strong non-periodicity, a critical property for secure cryptographic applications. The proposed approach combines the unpredictability of quantum chaos with the scalability of classical simulation, offering a practical and efficient alternative for secure random number generation.
This paper presents a novel approach to hardware security key generation leveraging the unique properties of quantum chaos. Traditional hardware security key generation methods often rely on pseudo-random number generators (PRNGs) which are susceptible to various attacks. Quantum chaos, arising from the inherent sensitivity to initial conditions in chaotic systems, offers a fundamentally different approach, providing a source of high-quality randomness and inherent robustness. This research details the design and implementation of a hardware system specifically engineered to generate quantum chaotic signals, followed by a method for extracting a cryptographic key based on the statistical characteristics of these signals. The core claim of this work is the generation of hardware security keys with high key authenticity. The key mechanism involves a stable quantum chaos signal generation system combined with statistical key extraction. The resulting keys are expected to demonstrate superior security characteristics compared to those generated by conventional PRNGs. This approach addresses the vulnerabilities inherent in existing hardware security solutions and provides a promising pathway toward more robust and secure key generation. ---
This paper explores the generation of high-quality random numbers utilizing the principles of quantum chaos. Traditional random number generators often exhibit limitations in terms of randomness and predictability, posing challenges for applications in secure communication and cryptography. This research investigates the potential of quantum chaos to overcome these limitations, proposing a novel approach based on quantum chaotic algorithms. The core of this approach lies in the generation of sequences exhibiting chaotic properties, subsequently analyzed to extract random numbers. The generated numbers are characterized by their enhanced randomness and unpredictability, offering a significant advancement over conventional methods. This work outlines the theoretical framework, the underlying mathematical principles, and the potential applications of quantum chaotic random number generation. The primary goal is to demonstrate a method capable of producing truly random sequences, crucial for secure systems.
This paper explores the design of cryptographic algorithms leveraging the inherent randomness of quantum random number generators (QRNGs). Traditional cryptographic algorithms often rely on pseudo-random number generators (PRNGs), which are deterministic and therefore vulnerable to attacks if their internal state is compromised. QRNGs, on the other hand, derive their randomness from quantum mechanical phenomena, offering a fundamentally unpredictable source of numbers. This research investigates the application of QRNGs to enhance cryptographic security, focusing on constructing algorithms that exploit this unique property. The core claim is that utilizing QRNG characteristics allows for the design of more secure cryptographic algorithms. The proposed mechanism involves capitalizing on the non-deterministic nature of QRNGs to build algorithms with heightened security levels. This approach presents a novel security guarantee method by incorporating true randomness into cryptographic processes. We examine specific algorithm designs and analyze their security implications compared to traditional PRNG-based approaches. The paper concludes with a discussion on the challenges and future directions of utilizing QRNGs in cryptography.
In this paper, we investigate the potential application of quantum computation for constructing pseudo-random number generators (PRNGs) and further construct a novel PRNG based on quantum random walks (QRWs), a famous quantum computation model. The PRNG merely relies on the equations used in the QRWs, and thus the generation algorithm is simple and the computation speed is fast. The proposed PRNG is subjected to statistical tests such as NIST and successfully passed the test. Compared with the representative PRNG based on quantum chaotic maps (QCM), the present QRWs-based PRNG has some advantages such as better statistical complexity and recurrence. For example, the normalized Shannon entropy and the statistical complexity of the QRWs-based PRNG are 0.999699456771172 and 1.799961178212329e-04 respectively given the number of 8 bits-words, say, 16Mbits. By contrast, the corresponding values of the QCM-based PRNG are 0.999448131481064 and 3.701210794388818e-04 respectively. Thus the statistical complexity and the normalized entropy of the QRWs-based PRNG are closer to 0 and 1 respectively than those of the QCM-based PRNG when the number of words of the analyzed sequence increases. It provides a new clue to construct PRNGs and also extends the applications of quantum computation.
In the era of digitization secure transmission of digital images has become essential in real world applications. Image encryption is an effective technique for protecting image data from unauthorized access. The security of encrypted data strongly depends on the quality of the random numbers used as the encryption key. In this paper, we proposed a hybrid random number generator based on quantum fluctuations and an algorithmically inspired rotating wheel. The wheel contains integer values from 0 to 255 that are shuffled using quantum fluctuations generated by time-evolving the quantum kicked rotor model. There are four pre-defined tapping positions in the rotating wheel to collect the number sequences. The wheel rotation speed is dynamically varied after each set of tapping to enhance unpredictability. The entropy of the number sequence obtained from the rotating wheel attains the ideal value of 8 (in an 8 bit representation). Further, the generated number sequences exhibit a flat histogram and nearly zero correlation, indicating strong randomness. The generated sequences are applied to the image encryption and analyzed cryptographically. Experimental results demonstrate a near ideal entropy of 7.997, an NPCR of 99.60%, low correlation in all directions, and low PSNR for encrypted images. These results confirm that the proposed random number generator achieves efficient and high-security performance, making it suitable for the security of consumer applications such as mobile healthcare imaging, biometric authentication, QR-based and multimedia communication on smart devices.
Random Number Generators (RNGs) are used in various applications, including cryptography, scientific simulations, gaming, and virtual reality. The quality of these random numbers is crucial, especially for computational approaches that rely on unpredictability to produce accurate results. In this thesis, we perform a comprehensive assessment of the quality of a novel Quantum Random Number Generator (QRNG) based on single photon. QRNGs leverage quantum mechanical properties to produce truly random numbers. This ensures high entropy, unpredictability, and security, making QRNGs particularly useful in fields that require high-quality randomness.We evaluate the statistical properties of strings generated by our QRNG and then its practical application by comparing it to traditional Pseudo-Random Number Generators (PRNGs) in Monte Carlo Integration (MCI), a technique that estimates integrals using random sampling. In particular, we use two statistical randomness test suits, namely NIST and Dieharder, to assess the statistical properties of our QRNG. All tests within these tests were passed, confirming that the corresponding QRNG achieves true randomness with sufficient high entropy. Next, we use our QRNG-generated numbers to seed Monte Carlo Integration (MCI) and compare it against results obtained using classical PRNG. The QRNG-based MCI demonstrated more accurate and stable numerical estimates, showing lower error rates and improved convergence compared to PRNG-based simulations.These findings highlight the advantages of QRNGs in enhancing numerical accuracy and computational security. While QRNGs may have slower generation rates than PRNGs, their superior randomness quality allows for more reliable Monte Carlo-based simulations, suggesting that fewer samples may be needed to achieve the same level of accuracy compared to classical PRNGs. This research underscores the potential of QRNG-powered numerical methods, paving the way for their integration into more advanced applications, including scientific computing, financial modeling, and cryptographic security.