Horizontal Correlation Research Articles

Power Analysis on NTRU Prime

This paper applies a variety of power analysis techniques to several implementations of NTRU Prime, a Round 2 submission to the NIST PQC Standardization Project. The techniques include vertical correlation power analysis, horizontal indepth correlation power analysis, online template attacks, and chosen-input simple power analysis. The implementations include the reference one, the one optimized using smladx, and three protected ones. Adversaries in this study can fully recover private keys with one single trace of short observation span, with few template traces from a fully controlled device similar to the target and no a priori power model, or sometimes even with the naked eye. The techniques target the constant-time generic polynomial multiplications in the product scanning method. Though in this work they focus on the decapsulation, they also work on the key generation and encapsulation of NTRU Prime. Moreover, they apply to the ideal-lattice-based cryptosystems where each private-key coefficient comes from a small set of possibilities.

Modeling Virus Transport and Removal during Storage and Recovery in Heterogeneous Aquifers

A quantitative understanding of virus removal during aquifer storage and recovery (ASR) in physically and geochemically heterogeneous aquifers is needed to accurately assess human health risks from viral infections. A two-dimensional axisymmetric numerical model incorporating processes of virus attachment, detachment, and inactivation in aqueous and solid phases was developed to systematically evaluate the virus removal performance of ASR schemes. Physical heterogeneity was considered as either layered or randomly distributed hydraulic conductivities (with selected variance and horizontal correlation length). Geochemical heterogeneity in the aquifer was accounted for using Colloid Filtration Theory to predict the spatial distribution of attachment rate coefficient. Simulation results demonstrate that the combined effects of aquifer physical heterogeneity and spatial variability of attachment rate resulted in higher virus concentrations in the recovered water at the ASR well (i.e. reduced virus removal). While the sticking efficiency of viruses to aquifer sediments was found to significantly influence virus concentration in the recovered water, the solid phase inactivation under realistic field conditions combined with the duration of storage phase had a predominant influence on the overall virus removal. The relative importance of physical heterogeneity increased under physicochemical conditions that reduced virus removal (e.g. lower value of sticking efficiency or solid phase inactivation rate). This study provides valuable insight on site selection of ASR projects and an approach to optimize ASR operational parameters (e.g. storage time) for virus removal and to minimize costs associated with post-recovery treatment.

Cone penetration test (CPT)-based subsurface soil classification and zonation in two-dimensional vertical cross section using Bayesian compressive sampling

A novel method is developed in this study for soil classification and zonation in a two-dimensional (2D) vertical cross section using cone penetration tests (CPTs). A CPT is usually performed vertically and the number of CPT soundings in a site is often limited in geotechnical engineering practice. It is, therefore, difficult to properly interpret CPT results along the horizontal direction or accurately estimate the horizontal correlation length of CPT data. The method proposed in this study bypasses the difficulty in estimating horizontal correlation length and provides proper identification of subsurface soil stratification (i.e., soil layer number is constant along horizontal direction) and zonation (i.e., soil layer number varies along horizontal direction) in a 2D vertical cross section directly from a limited number of CPT soundings. The proposed method consists of three key elements: 2D interpolation of CPT data using 2D Bayesian compressive sampling; determination of soil behavior type (SBT) using a SBT chart at every location in the 2D section, including locations with measurements and unsampled locations; and soil layer or zone delineation using an edge detection method. Both simulated and real data examples are used to illustrate the proposed method. Results show that the method performs well even when only five sets of CPT soundings are available.

Automatic generation of HCCA-resistant scalar multiplication algorithm by proper sequencing of field multiplier operands

Horizontal collision correlation analysis, in short HCCA, imposes a serious threat to simple power analysis-resistant elliptic curve cryptosystems involving unified algorithms, e.g., Edwards curve unified formula. This attack can be mounted even in the presence of differential power analysis-resistant randomization schemes. In this paper, we have designed an effective countermeasure for HCCA protection, where the dependency of side-channel leakage from a school–book multiplication with the underlying multiplier operands is investigated. We have shown how changing the sequence in which the operands are passed to the multiplication algorithm introduces dissimilarity in the information leakage. This disparity has been utilized in constructing a minimal cost countermeasure against HCCA. This countermeasure integrated with an effective randomization method has been shown to successfully thwart HCCA. Additionally we provide experimental validation for our proposed countermeasure technique on a SASEBO platform. To the best of our knowledge, this is the first time that asymmetry in information leakage has been utilized in designing a side-channel countermeasure.

Fault diagnosis of power grids based on grey relational analysis

A fault diagnosis method of power grids was presented based on grey relational analysis in this paper. For each suspected fault line in the power cut area, the grey relational of original characteristics sequence, amplitude and energy are calculated by using the current sampling value before and after the fault time. Then an active reference line was selected, followed by the calculation of the horizontal grey correlation between reference line and suspected fault line according to current sampling after the fault. Finally, the longitudinal grey relational degree and the horizontal grey relational degree of each line are weighted and fused to obtain their comprehensive grey relational degree, and the fault criterion is given to identify the faulty component accurately. The simulation results of the IEEE 14-node system show that the fault elements can be identified under different fault locations, various fault types and different transition resistances accurately.

Observing Mesospheric Turbulence With Specular Meteor Radars: A Novel Method for Estimating Second‐Order Statistics of Wind Velocity

There are few observational techniques for measuring the distribution of kinetic energy within the mesosphere with a wide range of spatial and temporal scales. This study describes a method for estimating the three‐dimensional mesospheric wind field correlation function from specular meteor trail echoes. Each radar echo provides a measurement of a one‐dimensional projection of the wind velocity vector at a randomly sampled point in space and time. The method relies on using pairs of such measurements to estimate the correlation function of the wind with different spatial and temporal lags. The method is demonstrated using a multistatic meteor radar data set that includes ≈105 meteor echoes observed during a 24‐hr time period. The new method is found to be in good agreement with the well‐established technique for estimating horizontal mean winds. High‐resolution correlation functions with temporal, horizontal, and vertical lags are also estimated from the data. The temporal correlation function is used to retrieve the kinetic energy spectrum, which includes the semidiurnal mode and a 3‐hr period wave. The horizontal and vertical correlation functions of the wind are then used to derive second‐order structure functions, which are found to be compatible with the Kolmogorov prediction for spectral distribution of kinetic energy in the turbulent inertial range. The presented method can be used to extend the capabilities of specular meteor radars. It is relatively flexible and has a multitude of applications beyond what has been shown in this study.

The Influence of Soil Stochastic Heterogeneity and Facility Dimensions on Stormwater Infiltration Facilities Performance

The progressive increase of impervious surfaces induced by urbanization altered significantly the natural hydrological cycle of urban catchments. To face the need of more sustainable and effective solutions for stormwater management and planning, Low Impact Development (LID) practices have been frequently proposed to support existing urban drainage systems. Among LID infrastructures, design and management of stormwater infiltration facilities are still characterised by a high degree of uncertainty. Since the stochastic heterogeneity of the soil may affect significantly their hydraulic performance, it is crucial to understand whether it should be accounted for in the design process. To this aim, numerical experiments under transient variably water saturated conditions were performed. Four infiltration facilities of different bottom length subjected to the same spatial variability of the intrinsic permeability field were considered. Simulations showed that the effects of stochastic heterogeneity on the hydraulic performance are dependent on the dimensions of the facility and on the correlation lengths of the intrinsic permeability field. These effects may potentially undermine the capacity to capture stormwater. To be reduced, the bottom dimensions of the facility should be higher than the horizontal correlation lengths of the intrinsic permeability field. Most strikingly, whether the stochastic heterogeneity is considered or not, the volume infiltrated through the bottom follows an increasing power law with increasing bottom length, while the average infiltration rate at the bottom follows a decaying power law.

Two-Dimensional Random Field Conditioned by CPT Data: Case Study

The presented geotechnical random field (GRF) algorithm is utilized to realize the soil inherent variability based on in situ site investigation results. This paper aims at investigating the effect of cone penetration test (CPT) borehole arrangements in horizontal plane on slope stability reliability analysis considering stochastic fields of soil design parameters via the conventional stationary along with the non-stationary random field adopted in the GRF approach. An advantage of the GRF algorithm is that it yields conservative results in comparison to the conventional stationary random field theory; therefore, using non-stationary random field underestimates slope stability reliability. The current study tried to highlight the importance of the availability of in situ profiles of soil strength parameters when stability analysis of geotechnical structures is concerned. Slope stability was chosen to interpret the role of the CPT profiles in the adjacent site in determining the factor of safety of the slope against shear failure. Furthermore, the results of the case under study showed that when the geometric dimensions of the slope are too small compared to the horizontal correlation length, more CPT borehole data availability leads only to very slightly conservative results in comparison to the case with single available CPT profile.

Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data

Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix. For the data space, signal polarization information can be used to evaluate the data uncertainties. The inversion forces the synthetic data to fit the polarization of observed data. A synthetic inversion for a 2D-2C data estimating a 1D elastic model shows a clear improvement, especially at the level of the receivers. For the model space, horizontal and vertical spatial correlations using a Laplace distribution can be used to fill the model space covariance matrix. This approach reduces the degree of freedom of the inverse problem, which can be quantitatively evaluated. Strong horizontal spatial correlation distances favor a tabular geological model whenever it does not contradict the data. The relaxation of the spatial correlation distances from large to small during the iterative inversion process allows the recovery of geological objects of the same size, which regularizes the inverse problem. Synthetic constrained and unconstrained inversions for 2D-2C crosswell data show the clear improvement of the inversion results when constraints are used.

Profile measurement of circulating electrons in a synchrotron by inserting a carbon wire

An internal radiator made of a carbon wire is employed to produce bremsstrahlung-photon beams for meson photoproduction experiments from circulating electrons in a synchrotron at the Research Center for Electron Photon Science, Tohoku University. The horizontal electron-beam size at the radiator location is determined from the decay rate of the resultant photon intensity as a function of the distance between the fixed position of the radiator and the centroid of the electron beam. The horizontal beam size at the radiator location is determined to be 0.74 mm with a statical error less than 0.01 mm for 1.3-GeV circulating electrons. The horizontal correlation between the position and momentum direction of the electron beam is also measured. The horizontal size and correlation are well-reproduced by the design values of the parameters of the synchrotron.

Horizontal spatial correlation of reverberation for rough sea-bottom interface

Correlation sonar, which estimates the velocity of vessel utilizing the principle of waveform invariance, can achieve the sampling of the horizontal spatial correlation of sea-bottom reverberation. The horizontal spatial correlation can be expressed as a correlation function and is affected by sea-bottom characteristics. The expression of the correlation function of the sea-bottom reverberation is derived, which is written as the convolution of the autocorrelation function of transmitted signal, the cross-correlation function of the backscattered impulse response from a plane interface, and the autocorrelation function of the probability density function of the sea-bottom roughness. The isotropic interface roughness of the sea-bottom leads to a circular planform of the correlation function whose width varies with roughness. The anisotropic interface roughness of the sea-bottom leads to an elliptical planform of the correlation function whose major axis is in the direction of weaker roughness. Simulation of submarine reverberation and correlation function verifies this conclusion. The model for the spatially covariant field is used to estimate the backscattering cross section which varies with azimuth angle under the condition of anisotropic seafloor roughness. It should be noted that the horizontal spatial correlation of reverberation is also related to sonar parameters and other sea-bottom characteristics.

An Investigation of Ocean Model Uncertainties Through Ensemble Forecast Experiments in the Southwest Atlantic Ocean

AbstractOcean general circulation models even with realistic behavior still incorporate large uncertainties from external forcing. This study involves the realization of ensemble experiments using a regional model configured for the Southwest Atlantic Ocean to investigate uncertainties derived from the external forcing such as the atmosphere and bathymetry. The investigation is based on perturbing atmospheric surface fluxes and bathymetry through a series of ensemble experiments. The results showed a strong influence of the South Atlantic Convergence Zone on the underlying ocean, 7 days after initialization. In this ocean region, precipitation and radiation flux perturbations notably impacted the sea surface salinity and sea surface temperature, by producing values of ensemble spread that exceeded 0.08 and 0.2 °C, respectively. Wind perturbations extended the impact on currents at surface, with the spread exceeding 0.1 m/s. The ocean responded faster to the bathymetric perturbations especially in shallow waters, where the dynamics are largely dominated by barotropic processes. Ensemble spread was the largest within the thermocline layer and in ocean frontal regions after a few months, but by this time, the impact on the modeled ocean obtained from either atmospheric or bathymetric perturbations was quite similar, with the internal dynamics dominating over time. In the vertical, the sea surface temperature exhibited high correlation with the subsurface temperature of the shallowest model levels within the mixed layer. Horizontal error correlations exhibited strong flow dependence at specific points on the Brazil and Malvinas Currents. This analysis will be the basis for future experiments using ensemble‐based data assimilation in the Southwest Atlantic Ocean.

Networked correlation-aware manufacturing service supply chain optimization using an extended artificial bee colony algorithm

Manufacturing service supply chain (MSSC) optimization has been intensively studied to find an optimal service composition solution with the best quality of service (QoS) value. However, traditional MSSC optimization methods usually assume that candidate services are independent of one another. Therefore, potentially better MSSC solutions may have been neglected by not considering the positive influence of correlations between services on the QoS value. This study proposes a novel networked correlation-aware manufacturing service composition (NCMSC) mathematical model to characterize the influence of vertical and horizontal correlations between services on the QoS value of MSSC solution. To solve the NCMSC model, an extended artificial bee colony (ABC) algorithm is proposed to find a near-optimal solution with the best QoS value. The specific improvements to the original ABC algorithm include the following: (1) a new matrix-based encoding scheme is proposed to describe the MSSC solution in which each column contains a vertical composite structure and collaborative services for each subtask; (2) the migration operator of a biogeography-based optimization algorithm is combined with the original ABC algorithm to address the discrete MSSC optimization problem and improve the performance of the original ABC algorithm. The results of the experiments illustrate the importance of networked correlations between services, better practicality, effectiveness, and efficiency of the extended ABC algorithm in solving the optimization problem of MSSC.

Encryption of medical image with most significant bit and high capacity in piecewise linear chaos graphics

Along with the development of cloud computing, data privacy has become the focus of attention. However, the existing methods do not allow large amounts of information to be hidden in reversible ways. In this paper, a MSB prediction-based high-capacity reversible data hiding image encryption algorithm is put forward. Due to the local correlation between the pixels and their adjacent areas in a clear image, the value of adjacent two pixels are very close. For this reason, it seems reasonable to predict pixel values by using previously decrypted images, just as many image encoding and compression methods. However, in some cases, there are some errors. Therefore, the first step of the algorithm includes identifying all prediction errors in the original image and storing the information in a binary map of the error locations. After that, a high-capacity reversible data hiding method (CPHCRDH) is proposed to correct the prediction error. This method first conducts the prediction error correction before encryption, and preprocesses the original image according to the error location map to avoid all prediction errors, and then encrypts the pre-processed image. The clear image can be reconstructed without damage through MSP prediction. Finally, through the simulation experiment on three selected CT image test examples of the eyes, body and brain, it is shown that the proposed method is significantly superior to the selected contrasted algorithm in six indicators such as the horizontal and vertical correlation coefficients.

Side-Channel Vulnerabilities of Unified Point Addition on Binary Huff Curve and Its Countermeasure

Unified point addition for computing elliptic curve point addition and doubling is considered to be resistant to simple power analysis. Recently, new side-channel attacks, such as recovery of secret exponent by triangular trace analysis and horizontal collision correlation analysis, have been successfully applied to elliptic curve methods to investigate their resistance to side-channel attacks. These attacks turn out to be very powerful since they only require leakage of a single power consumption trace. In this paper, using these side-channel attack analyses, we introduce two vulnerabilities of unified point addition on the binary Huff curve. Also, we propose a new unified point addition method for the binary Huff curve. Furthermore, to secure against these vulnerabilities, we apply an equivalence class to the side-channel atomic algorithm using the proposed unified point addition method.

Revisiting Fisher's approach to the handling of horizontal spatial correlations of observation errors in a variational framework

A long‐standing issue in atmospheric data assimilation is that only a fraction of the available observations are used in the analysis. This is especially true for satellite data, which undergo channel selection and are thinned to coarser spatial and temporal resolutions. Up to now, horizontal spatial correlations of observation errors have not been fully accounted for. However, we may expect progress in forecast quality from the assimilation of spatially dense no‐thinned data while accounting for correlated errors, as this may provide a better constraint on the initial conditions at smaller scales.This article addresses the handling of the observation‐error covariance matrix when the number of observations is large (e.g. above a few thousand). In variational methods, the analysis usually requires evaluation of products with the inverse observation‐error covariance matrix; however, the lack of structure and the size of the problem make it difficult to invert this matrix with direct approaches.A method has been proposed several years ago by M. Fisher, in which an observation‐error covariance matrix is built from a sequence of operators. The Lanczos algorithm is then used to provide a low‐rank eigenvalue decomposition of the correlation matrix, which is regularized and explicitly inverted. This article elaborates on this method, with application to the so‐called Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation for the convective‐scale model of Météo‐France.We analyze the implications of truncating the eigenspectrum. We show that both the modelled spatial correlations and the variances are affected by truncation noise. The noise in the variance, in particular, is linked with the local density of the observations. Overall, several hundred eigenpairs may be required to obtain a fair representation of the covariances. While computationally expensive, this method can be used as a baseline to evaluate other approaches.

Ensemble-Based Atmospheric Reanalysis Using a Global Coupled Atmosphere–Ocean GCM

ABSTRACT Ensemble-based atmospheric data assimilation (DA) systems are sometimes afflicted with an underestimation of the ensemble spread near the surface caused by the use of identical boundary conditions for all ensemble members and the lack of atmosphere–ocean interaction. To overcome these problems, a new DA system has been developed by replacing an atmospheric GCM with a coupled atmosphere–ocean GCM, in which atmospheric observational data are assimilated every 6 h to update the atmospheric variables, whereas the oceanic variables are subject to no direct DA. Although SST suffers from the common biases among many coupled GCMs, two months of a retrospective analysis–forecast cycle reveals that the ensemble spreads of air temperature and specific humidity in the surface boundary layer are slightly increased and the forecast skill in the midtroposphere is rather improved by using the coupled DA system in comparison with the atmospheric DA system. In addition, surface atmospheric variables over the tropical Pacific have the basinwide horizontal correlation in ensemble space in the coupled DA system but not in the atmospheric DA system. This suggests the potential benefit of using a coupled GCM rather than an atmospheric GCM even for atmospheric reanalysis with an ensemble-based DA system.

Estimating the Correlated Observation-Error Characteristics of the Chinese FengYun Microwave Temperature Sounder and Microwave Humidity Sounder

In operational data assimilation systems, observation-error covariance matrices are commonly assumed to be diagonal. However, inter-channel and spatial observation-error correlations are inevitable for satellite radiances. The observation errors of the Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) onboard the FengYun-3A (FY-3A) and FY-3B satellites are empirically assigned and considered to be uncorrelated when they are assimilated into the WRF model’s Community Variational Data Assimilation System (WRFDA). To assimilate MWTS and MWHS measurements optimally, a good characterization of their observation errors is necessary. In this study, background and analysis residuals were used to diagnose the correlated observation-error characteristics of the MWTS and MWHS. It was found that the error standard deviations of the MWTS and MWHS were less than the values used in the WRFDA. MWTS had small inter-channel errors, while MWHS had significant inter-channel errors. The horizontal correlation length scales of MWTS and MWHS were about 120 and 60 km, respectively. A comparison between the diagnosis for instruments onboard the two satellites showed that the observation-error characteristics of the MWTS or MWHS were different when they were onboard different satellites. In addition, it was found that the error statistics were dependent on latitude and scan positions. The forecast experiments showed that using a modified thinning scheme based on diagnosed statistics can improve forecast accuracy.

Analysis of sonar clutter using backscattered spatial correlation

Sonar clutter events are one of the primary limitations of long-range active sonar systems within the littoral environment. For this reason, research towards understanding their acoustic return characteristics and ultimately their mitigation are of high importance. This paper discusses measurements and modeling of the backscattered horizontal correlation function from clutter events and comparison with returns from the littoral environment. A statistical model for returns from boundaries, as well as general expectations of returns from common clutter sources will be discussed. The horizontal correlation function is estimated via sub-aperture beamforming of the Five Octave Research Array (FORA), a towed line array system owned and operated by Penn State and funded by the Office of Naval Research. [Work supported by Office of Naval Research.]

Analysis on acoustic longitudinal horizontal correlation of air-to-water transmission

Spatial correlation is an important characteristic of underwater sound field, which is relevant to the detection of aerial targets from underwater. But compared with waterborne sources there are few researches about airborne sources. In order to perform further analysis on the air-to-water sound transmission in shallow water, State Key Laboratory of Acoustics, Institute of Acoustics, conducted an experiment in the South China Sea in March, 2013. During the experiment, multi-frequency signals transmitted by a hooter hung on a research ship were received by a horizontal line array (HLA) which laid on the seabottom, and signals far from 9.8 km were received successfully. Based on data recorded in the experiment, the longitudinal horizontal correlation coefficients of underwater sound field excited by airborne source at different distances with the frequency is 128 Hz are obtained, which have evident oscillation structure as horizontal spacing increases. The mathematical expression is derived based on the normal mode theory and gives a better physical explanation for the oscillatory behavior of the experimental longitudinal horizontal correlation.