Linear-feedback shift register (LFSR) based pseudo-random number generator (PRNG) has applications in a plethora of fields. The issue of being linear is generally circumvented by introducing non-linearities as per the required applications, with some being adhoc but fulfilling the purpose while others with a theoretical proof. The goal of this study is to develop a sufficiently ``random" resource for Quantum Key Distribution (QKD) applications with a low computational cost. However, as a byproduct, we have also studied the effect of introducing minimum non-linearity with experimental verification. Starting from the numerical implementation to generate a random sequence, we have implemented a XOR of two LFSR sequences on a low-cost FPGA evaluation board with one of the direct use cases in QKD protocols. Such rigorously tested random numbers could also be used like artificial neural networks or testing of circuits for integrated chips and directly for encryption for wireless technologies.
Linear-feedback shift register (LFSR) based pseudo-random number generator (PRNG) has applications in a plethora of fields. The issue of being linear is generally circumvented by introducing non-linearities as per the required applications, with some being adhoc but fulfilling the purpose while others with a theoretical proof. The goal of this study is to develop a sufficiently ``random" resource for Quantum Key Distribution (QKD) applications with a low computational cost. However, as a byproduct, we have also studied the effect of introducing minimum non-linearity with experimental verification. Starting from the numerical implementation to generate a random sequence, we have implemented a XOR of two LFSR sequences on a low-cost FPGA evaluation board with one of the direct use cases in QKD protocols. Such rigorously tested random numbers could also be used like artificial neural networks or testing of circuits for integrated chips and directly for encryption for wireless technologies.
Reversible logic gates are critical components in the field of quantum computing and low-power digital circuits, as they allow for the retrieval of input states from output states without any loss of information. This property ensures minimal energy dissipation, aligning with the principles of reversible computation. Their applications extend to quantum computing, cryptographic systems, and error detection and correction mechanisms. This paper presents a novel design for a Reversible D Flip-Flop (RDFF) and a 4-bit Linear Feedback Shift Register (LFSR). The Linear Feedback Shift Register (LFSR) is built utilizing four Register-Driven D Flip-Flops (RDFFs) and a feedback mechanism that incorporates a Feynman Gate. This configuration successfully showcases the capacity to generate pseudo-random sequences. The LFSR design demonstrates a 10% improvement in Total Reversible Logic Implementation Cost and 27% enhancement in quantum cost, making it a more resource-efficient option for reversible computing. This work makes a valuable contribution to the field of reversible computing by offering efficient designs for essential components.
Generating reliable random and pseudo-random sequences is important in many electronic and signal processing systems, such as secure communications, radar, spread-spectrum methods, and autonomous platforms. Although true and quantum random number generators provide stronger unpredictability, classical pseudo-random number generators, including Linear Feedback Shift Registers (LFSRs) and the Mersenne Twister (MT), are still widely used because they are efficient and easy to implement. This work introduces a user-friendly software platform for generating, analyzing, and evaluating the predictability of pseudo-random bit sequences. The software supports two main functions: generating sequences using classical PRNGs and hybrid combinations, and analyzing input sequences through statistical measures and data-driven methods. In particular, hybrid LFSR-MT structures are studied to examine how they affect sequence complexity and resistance to prediction. The platform also includes machine-learning and deep-learning tools to investigate when deterministic PRNGs may remain partially predictable, even when their structure becomes more complex. The results show that algorithmic random sequence generators have inherent limitations in terms of unpredictability, which supports the use of quantum random sequences in security-critical applications. A comparative study between classical LFSR-MT sequences and quantum random sequences shows that quantum randomness offers higher unpredictability due to its non-deterministic physical origin. The potential use of quantum random sequences in jamming applications is also discussed, highlighting their improved robustness against prediction-based attacks. Overall, the proposed software provides a practical tool for analyzing, comparing, and benchmarking random sequence generators in modern electronic, sensing, and quantum-enabled communication systems.
Recently, there has been a growing interest among researchers in Pseudo-Random Binary Sequences (PRBS) for Quantum Key Distribution (QKD). QKD is a cryptographic protocol that distributes secret keys between senders and receivers, relying on random numbers to determine the basis for evaluating transmitted bits. Quantum Random Number Generators (QRNG) utilizing natural resources create random bit sequences for QKD. However, QRNGs are susceptible to natural noise, which compromises their security. Additionally, post-processing of QRNG-generated sequences is necessary to reduce noise, but this process slows down the random number generation speed in QKD. Non-deterministic Pseudo-Random Sequence Generators (ND-PRSG) may overcome the QRNG's constraints, post-processing, and speed. Lattice-based NDPRSG provides security and efficiency. The proposed work focuses on generating a uniform PRBS with non-deterministic entropy using Learning with Errors (LWE) and LFSR. NIST Statistical Tests are performed on generated PRBS for randomness analysis, and the results are reported. The proposed PRBS generation can be used for QKD, operating up to 20.17 Mbit/s.
A quantum stream cipher by Yuen 2000 (Y-00) protocol with a feedback shift register - a linear feedback shift register (LFSR) or a nonlinear feedback shift register - is very attractive in implementing a secure high-speed optical data transmission system for next-generation optical networking. So far, a LFSR has been used in a quantum stream cipher by Y-00 as a running key generator, rather than a nonlinear feedback shift register. But, it is well-known that an appropriately designed nonlinear feedback shift register has larger period and linear complexity than the corresponding quantities of a LFSR driven by a secret key of the same length. Although large linear complexity of a key generator does not immediately guarantee the security of the key generator itself, it forces the eavesdropper at least to collect more measurement data to carry out the attacks. This motivates us to use a nonlinear feedback shift register as a running key generator in a quantum stream cipher by Y-00. The purpose of this study is to make a quantum stream cipher more costly in terms of cryptoanalysis, enhancing the advantages of using a nonlinear feedback shift register. For this purpose, we propose a new randomization technique for a running key generator in this paper. First, we state the basics of a quantum stream cipher by Y-00. Second, we propose the randomization on a running key consisting of two different type of basis converter. To evaluate the effect of the randomization in terms of the amount of information that is extracted by her measurement, numerical simulation is performed in the cases of an optical heterodyne receiver and a quantum optimal receiver under the assumption that the eavesdropper knows plaintext. Finally, we summarize the results.
Nano industries have been successful trendsetters for the past 30 years, in escalating the speed and dropping the power necessities of nanoelectronic devices. According to Moore's law and the assessment created by the international technology roadmap for semiconductors, beyond 2020, there will be considerable restrictions in manufacturing IC's based on CMOS technologies. As a result, the next prototype to get over these effects is quantum-dot cellular automata (QCA). In this chapter, an efficient quantum cellular automata (QCA) based random number generator (RNG) is proposed. QCA is an innovative technology in the nano regime which guarantees large device density, less power dissipation, and minimal size as compared to the various CMOS technologies. With the aim to maximise the randomness in the proposed nano communication, a linear feedback shift register (LFSR) keyed multiplexer with ring oscillators is developed. The developed RNG is simulated using a quantum cellular automata (QCA) simulator tool.
Random number generators (RNGs) are notoriously challenging to build and test, especially for cryptographic applications. While statistical tests cannot definitively guarantee an RNG's output quality, they are a powerful verification tool and the only universally applicable testing method. In this work, we design, implement, and present various post-processing methods, using randomness extractors, to improve the RNG output quality and compare them through statistical testing. We begin by performing intensive tests on three RNGs-the 32-bit linear feedback shift register (LFSR), Intel's 'RDSEED,' and IDQuantique's 'Quantis'-and compare their performance. Next, we apply the different post-processing methods to each RNG and conduct further intensive testing on the processed output. To facilitate this, we introduce a comprehensive statistical testing environment, based on existing test suites, that can be parametrised for lightweight (fast) to intensive testing.