Random Source Research Articles

A true random number generator based on double threshold-switching memristors for image encryption

True random number generator (TRNG) that cannot be arbitrary attacked with predictable software algorithm is a promising data security solution. Memristors, possessing specific intrinsic stochasticity, are just appropriate to be the random sources for encryption applications. In this work, a TRNG system based on the stochastic duration time of double threshold-switching (TS) memristors is proposed. The reliable stochasticity of this system is mainly attributed to the gradual dissolution of Ag conductive channels and the synergistic effect of these two TS memristors. A digital circuit system based on the micro-controller unit is designed to produce stable random “0” and “1” bitstreams. The random data key generated by this double TS memristor TRNG passed the National Institute of Standards and Technology randomness tests without post-processing procedure. Taking advantage of the true random data key, the binary image can be encrypted and decrypted by executing the XNOR logic operation. In addition, the Gaussian noise effect on the decryption stability of image information secure communication is also analyzed. Although 90% Gaussian noise was applied to the original image, the pristine binary image still can be roughly recognized. This work demonstrates that the double TS memristors-based TRNG system has great potential for hardware security applications.

Rigidity of superdense coding

The famous superdense coding protocol of Bennett and Wiesner demonstrates that it is possible to communicate two bits of classical information by sending only one qubit and using a shared EPR pair. Our first result is that an arbitrary protocol for achieving this task (where there are no assumptions on the sender’s encoding operations or the dimension of the shared entangled state) is locally equivalent to the canonical Bennett-Wiesner protocol. In other words, the superdense coding task is rigid . In particular, we show that the sender and receiver only use additional entanglement (beyond the EPR pair) as a source of classical randomness. We also investigate several questions about higher-dimensional superdense coding, where the goal is to communicate one of d 2 possible messages by sending a d -dimensional quantum state, for general dimensions d . Unlike the d = 2 case (i.e. sending a single qubit), there can be inequivalent superdense coding protocols for higher d . We present concrete constructions of inequivalent protocols, based on constructions of inequivalent orthogonal unitary bases for all d > 2. Finally, we analyze the performance of superdense coding protocols where the encoding operators are independently sampled from the Haar measure on the unitary group. Our analysis involves bounding the distinguishability of random maximally entangled states, which may be of independent interest.

Non‐maturing deposits modelling in a Ornstein‐Uhlenbeck framework

AbstractThis paper builds a multivariate Lévy‐driven Ornstein‐Uhlenbeck process for the management of non‐maturing deposits, that are a major source of funding for banks. The contribution of the paper is both theoretical and operational. On the theoretical side, the novelty of this model is to include three independent sources of randomness in a Lévy framework: market interest rates, deposit rates and deposit volumes. The choice of a Lévy background driving process allows us to model rare but severe events. On the operational side, we propose a procedure to include severe volume outflows with positive probability in future scenarios simulation, explaining its implementation with an illustrative example using Italian banking sector data.

An Anonymous Authentication and Secure Communication Protocol in Ad-Hoc Networks

Abstract: The one-time pad (OTP) stable transmission is based at the random keys to acquire best secrecy, whilst the unpredictable wi-fi channel is proven to be an awesome random source. There is only a few paintings of the joint layout of OTP and key era from wi-fi channels. This paper presents a complete and quantitative research on stable transmission accomplished with the use of using OTP and wi-fi channel randomness. We recommend OTP stable transmission schemes, i.e., Identical Keyprimarily based totally Physical Layer Secure Transmission (IK-PST) and Un-Same Key-primarily based totally Physical-layer Secure Transmission (UK-PST). We quantitatively examine the overall performance of each schemes and show that UKPST outperforms IK-PST. We enlarge the pairwise techniques to a collection of customers in networks with super mega celebrity and chain topologies. We put in force prototypes of each schemes and examine the proposed schemes thru each simulations and experiments. The consequences confirm that UK-PST has a better powerful mystery transmission charge than that of IK-PST for situations with each pairwise and organization customers

Delocalized and dynamical catalytic randomness and information flow

We generalize the theory of catalytic quantum randomness to distributed and dynamical settings. First, we expand the theory of catalytic quantum randomness by calculating the amount of (R\'enyi) entropy catalytically extractable from a distributed or dynamical randomness source. We show that no entropy can be catalytically extracted when one cannot implement local projective measurement on randomness source without altering its state. As an application, we prove that quantum operation cannot be hidden in correlation between two parties without using randomness, which is the dynamical generalization of the no-hiding theorem. Moreover, the formalism of distributed catalysis is applied to develop a formal definition of semantic quantum information and it follows that utilizing semantic information is equivalent to catalysis using a catalyst already correlated with the transforming system. By doing so, we unify the utilization of semantic and nonsemantic quantum information and conclude that one can always extract more information from an incompletely depleted classical randomness source, but it is not possible for quantum randomness sources.

Distribution of sentence length and dependency distance in children's compositions: Characteristics of natural language and variations in language development

This study analyzed the distribution of the sentence length and mean of dependency distances (MDD) in Japanese sentences, comparing data from random sources with that obtained from children's compositions, and identifying changes in distribution according to grade level. Findings reveal that the sentence length in random data is well suited to a geometric distribution, whereas MDD is well suited to a lognormal distribution. In contrast, data from children's compositions show a shift in the distribution of the number of clauses from a lognormal to a gamma distribution, depending on the school year, with MDD suiting a gamma distribution. Mean MDD increases exponentially with the logarithm of the number of clauses in random data, while it increases linearly in composition data, thus generally supporting previous findings that dependency distances are optimized in natural language. However, MDDs exhibit non-monotonic changes with grades, suggesting the complexity of children's language development.

Changes in the statistical properties of electromagnetic double multi-Gaussian Schell-model beams on propagation in free space.

A class of electromagnetic random sources with a multi-Gaussian functional form in the spectral density and in the correlations part of the cross-spectral density matrix is introduced based on the genuine cross-spectral density-matrix theory. The analytic propagation formulas of the cross-spectral density matrix of such beams propagating in free space are derived by use of Collins' diffraction integral. With the help of analytic formulas, the evolution of statistical characteristics, i.e.,the spectraldensity, the spectral degree of polarization, and the spectral degree of coherence for such beams in free space are analyzed numerically. Employing the multi-Gaussian functional form in the cross-spectral density matrix introduces one more freedom in the modeling of Gaussian Schell-model sources.

Analysis of wind power output characteristics and output prediction

A fuzzy clustering method and a prediction correction method based on the Copula function are used to establish an analytical model of wind power generation output characteristics. It also predicts the expected and corrected values of its power generation to alleviate the pressure on the grid caused by the high proportion of random new energy sources connected to the grid. Based on the natural properties of wind, a new characteristic index based on the traditional load characteristic index and the new energy output curve is proposed to quantify and evaluate the characteristics of new energy power generation. The results show that the method proposed in this paper can effectively reduce the influence of climate change on output prediction; in comparison to the traditional index, the new index is more refined and instructive.

ANALISIS KREATIVITAS SISWA DALAM PEMBELAJARAN EKONOMI

The purpose of this study was to determine the Creativity of Class X IPA 2 SMAN 2 Sungai Raya in Economic Learning, namely in understanding the material and doing assignments. The research method in this study uses a qualitative approach. Qualitative research is a method used in natural object conditions, where the researcher is the key instrument in taking random data sources, triangulation techniques, qualitative data analysis and the results of research are more about meaning. the form of research used is a case study. The informants in this study were Subject Teachers and Class X IPA 2 Students at SMAN 2 Sungai Raya, namely 1 teacher and 18 students. Data collection techniques using direct interviews, observation and documentation. The results of this study indicate that when understanding the subject matter there are 9 students with a percentage of 50.00% who can fulfill the characteristics of creativity, namely Originality, Fluency, Flexibility, Elaboration, whereas when doing assignments there are 12 students with a percentage of 66.67% who are at level 3 which is very creative because they can fulfill the 3 components of creativity which consist of fluency, flexibility, and elaboration.

Combined Random Number Generator on Programmable Logic Integrated Circuits

The paper shows the practical possibility of implementing random number generators on field programmable gate arrays (FPGA) by combining various physically unclonable functions. A compact and scalable scheme of a digital random number source based on an asynchronous flip-flop of the D-type is proposed, which combines the characteristics of a static memory physically unclonable functions and a ring oscillator physically unclonable functions. Unlike existing random number generators, the proposed scheme can be used to solve the problem of unclonable identification of digital devices. The article presents experimental results obtained by the proposed generator circuit based on the FPGA Xilinx Zynq. The main modes of operation, probabilistic and statistical characteristics of numerical sequences, generated by the proposed scheme are described.

Towards passive non-line-of-sight acoustic localization around corners using uncontrolled random noise sources

Non-line-of-sight (NLoS) imaging is an important challenge in many fields ranging from autonomous vehicles and smart cities to defense applications. Several recent works in optics and acoustics tackle the challenge of imaging targets hidden from view (e.g. placed around a corner) by measuring time-of-flight information using active SONAR/LiDAR techniques, effectively mapping the Green functions (impulse responses) from several controlled sources to an array of detectors. Here, leveraging passive correlations-based imaging techniques (also termed ’acoustic daylight imaging’), we study the possibility of acoustic NLoS target localization around a corner without the use of controlled active sources. We demonstrate localization and tracking of a human subject hidden around a corner in a reverberating room using Green functions retrieved from correlations of broadband uncontrolled noise sources recorded by multiple detectors. Our results demonstrate that for NLoS localization controlled active sources can be replaced by passive detectors as long as a sufficiently broadband noise is present in the scene.

Physical-layer encryption and authentication scheme based on SKGD and 4D hyper-chaos.

In this paper, a scheme to realize encryption and digital identity authentication at the same time is proposed for enhancing the physical-layer security of point-to-point optical links (PPOL). Exploiting identity code encrypted by the key as authentication information effectively resists passive eavesdropping attacks in fingerprint authentication. The proposed scheme theoretically realizes secure key generation and distribution (SKGD) by phase noise estimation of the optical channel and the generation of identity codes with good randomness and unpredictability by the four-dimensional (4D) hyper-chaotic system. The local laser, erbium doped fiber amplifier (EDFA), and public channel provide the entropy source of uniqueness and randomness to extract symmetric key sequences for legitimate partners. The simulation conducted in a quadrature phase shift keying (QPSK) PPOL system over 100km standard single mode fiber verify successfully that 0.95Gbit/s error-free SKGD. The unpredictability and high sensitivity to the initial value and control parameters of the 4D hyper-chaotic system provide a huge space of ~10125 for identity codes, which is sufficient to resist exhaustive attack. With the proposed scheme, the security level of key and identity can be increased markedly.

Source-independent quantum random number generator against tailored detector blinding attacks.

Randomness, mainly in the form of random numbers, is the fundamental prerequisite for the security of many cryptographic tasks. Quantum randomness can be extracted even if adversaries are fully aware of the protocol and even control the randomness source. However, an adversary can further manipulate the randomness via tailored detector blinding attacks, which are hacking attacks suffered by protocols with trusted detectors. Here, by treating no-click events as valid events, we propose a quantum random number generation protocol that can simultaneously address source vulnerability and ferocious tailored detector blinding attacks. The method can be extended to high-dimensional random number generation. We experimentally demonstrate the ability of our protocol to generate random numbers for two-dimensional measurement with a generation speed of 0.1 bit per pulse.

Text Encryption Using Improving Key of Hi Sec Algorithm Using Rubik's Cube

Several techniques have been developed to generate keys using Rubik's Cube, which has been researched as a potential source of randomness for cryptography. This study suggests an innovative technique for creating a key for the Hi Sec algorithm using a Rubik's Cube image. The process entails creating a binary key for text encryption by leveraging the cube's color information. The Rubik's Cube principle, which includes choosing a subset of cube faces to generate the key, serves as the foundation for the key creation process. Experimental findings indicate that the proposed approach can produce safe keys that are resilient to a variety of assaults. The technique offers a fresh and effective way to generate keys for the Hi Sec algorithm, which may be used in several secure communication systems. The proposed method was programmed in VisualBaic.Net 2012.

An efficient method for generating a discrete uniform distribution using a biased random source

AbstractWe present an efficient algorithm to generate a discrete uniform distribution on a set of p elements using a biased random source for p prime. The algorithm generalizes Von Neumann’s method and improves the computational efficiency of Dijkstra’s method. In addition, the algorithm is extended to generate a discrete uniform distribution on any finite set based on the prime factorization of integers. The average running time of the proposed algorithm is overall sublinear: $\operatorname{O}\!(n/\log n)$ .

Statistics and probabilities for spectral analysis

Spectral analysis of data plays a central role in many signal processing applications, and comparing the relative output levels between filters often provides clues about the actual signals present in the data. Since data are often corrupted by noise, interference, or some other source of randomness, these filter outputs are also subject to random variations. Proper interpretation of these filter outputs is made possible by an awareness of the nature of their statistical variability. Thus, homework problems that illustrate how basic fundamental properties of random variables/vectors lend significant insight into the nature of such filter output comparisons are of great value in engineering practice. This talk will describe a handful of interesting problems that help with the interpretation of filtered data outputs used in some form of spectral analysis (e.g., FFT filters, beamformers, etc.). The problems considered will leverage notions of invariances, regeneration properties, and a basic algebra of random variables.

DeeR-Gen: A pseudo random number generator for Industry 4.0 / IoT

Random binary bit sequences or random numbers are very useful in cryptographic applications. These sequences are used as a key in different encryption algorithms. Also, they can be used as random nonce in many mutual authentication protocols. Because these sequences are used at very basic level in cryptographic applications there generation should be fast, secure, and energy-efficient. Particularly in the case of Industry 4.0/IoT, a lightweight implementation is much needed along with high security and rapid production. The earlier generators of random numbers used the true source of randomness but the same is not feasible in current scalable Industry 4.0/IoT scenario. Many works have already been done to generate random numbers through PRNGs. Some examples are J3Gen, Warbler, LAMED, and ARROW. However, it is essential to bring a completely programmed, highly secured, energy efficient and a fast paced algorithm for random number generation. In this paper, a novel algorithm, named DeeR-Gen, which works with one multiplexer and two NLFSRs is presented. It requires only 245 GE on ASIC, lowest hardware requirement till date. Proposed methodology has also been tested for EPC test of randomness. The authors found the proposed algorithm secure and energy-efficient to be used in any lightweight cryptographic algorithm.

Waveform Inversion of Shallow Seismic data with Randomly Selected Sources

Applying waveform inversion with randomly selected sources (RS) increases the convergence rate of the optimization process within full-waveform inversion (FWI) workflows and reduces overall computational time. FWI has been shown to be a valuable addition to the existing geophysical methods for near-surface characterization. Accurate 3D modeling of the (visco) elastic wavefield allows to diminish assumptions about wave propagation and include surface- and body-wave based arrivals within the inversion workflow. This approach could result in reliable high-resolution subsurface models, but generally it comes at a high computational cost for each individual source modeling. Commonly, multiple sources are involved in the inversion process, which proportionally increases the resulting computations for a time-domain FWI, but seismic data with dense source/receiver coverage usually contain redundant information. This is especially true for seismic near-surface applications, where the number of recorded sources per wavelength of interest are normally excessive. The inversion performance was increased by randomly selecting a subset of sources at each FWI iteration. The method's effectiveness is obvious on a FWI near-surface void detection application. Synthetic 2D experiments for fixed and rolling spreads showed comparable results with fewer calculations. The best performance was achieved when a single random source was used for each inversion iteration. The effectiveness of the method was also evident on a shallow 3D field dataset collected in the Sonora Desert in western Arizona, where data were acquired over a 10-m deep void with known location, orientation, and dimensions.

An inverse random source problem for the time-space fractional diffusion equation driven by fractional Brownian motion

Abstract We study the inverse random source problem for the time-space fractional diffusion equation driven by fractional Brownian motion with Hurst index H ∈ ( 0 , 1 ) {H\in(0,1)} . With the aid of a novel estimate, by using the operator approach we propose regularity analyses for the direct problem. Then we provide a reconstruction scheme for the source terms f and g up to sign. Next, combining the properties of Mittag-Leffler function, the complete uniqueness and instability analyses are provided. It is worth mentioning that all the analyses are unified for H ∈ ( 0 , 1 ) {H\in(0,1)} .

Sub-catchment-based urban flood risk assessment with a multi-index fuzzy evaluation approach: a case study of Jinjiang district, China

Urban flood risk assessment requires attention in inland areas with intensifying climate change and an increasing probability of extreme precipitation. This study describes the developments and testing of a sub-catchment-based multi-index fuzzy evaluation approach that can provide adaptation guidance for municipal decision-makers at a local level. We first built a comprehensive flood risk assessment system considering three categories: hazard, urban system, and social environment. The proposed evaluation system includes hybrid uncertain information that involves random indicator sources and hesitant fuzzy judgments from experts. The storm weather management model combined with geographic information system tools was then applied to obtain random indicators. Subsequently, hesitant fuzzy linguistic sets and the Euclidean distance method were adopted to solve the problem of uncertainty and vagueness from subjective hesitant information. Therefore, the aggregation method provides a beneficial way to assess flood risk in a hybrid uncertain environment. In addition, the proposed approach was applied to the Jinjiang district in an inland city in the P. R. of China. This supports efforts to prioritize locally tailored policies and practical measures for higher-risk sub-catchments within large urban systems.