Visualization of big data security： a case study on the KDD99 cup data set

Cyber security has been thrust into the limelight in the modern technological era because of an array of attacks often bypassing tmtrained intrusion detection systems （IDSs）. Therefore, greater attention has been directed on being able deciphering better methods for identifying attack types to train IDSs more effectively. Keycyber-attack insights exist in big data; however, an efficient approach is required to determine strong attack types to train IDSs to become more effective in key areas. Despite the rising growth in IDS research, there is a lack of studies involving big data visualization, which is key. The KDD99 data set has served as a strong benchmark since 1999; therefore, we utilized this data set in our experiment. In this study, we utilized hash algorithm, a weight table, and sampling method to deal with the inherent problems caused by analyzing big data; volume, variety, and velocity. By utilizing a visualization algorithm, we were able to gain insights into the KDD99 data set with a clear iden- tification of ＂normal＂ clusters and described distinct clusters of effective attacks.

13 Galactic Star Clusters in Gaia DR3 Identified by An Improved FoF and UPMASK Hybrid Method Using MvC

Open clusters(OCs)serve as invaluable tracers for investigating the properties and evolution of stars and galaxies.Despite recent advancements in machine learning clustering algorithms,accurately discerning such clusters remains challenging.We re-visited the 3013 samples generated with a hybrid clustering algorithm of FoF and pyUPMASK.A multi-view clustering(MvC)ensemble method was applied,which analyzes each member star of the OC from three perspectives—proper motion,spatial position,and composite views—before integrating the clustering outcomes to deduce more reliable cluster memberships.Based on the MvC results,we further excluded cluster candidates with fewer than ten member stars and obtained 1256 OC candidates.After isochrone fitting and visual inspection,we identified 506 candidate OCs in the Milky Way.In addition to the 493 previously reported candidates,we finally discovered 13 high-confidence new candidate clusters.

Cluster Analysis of the Roma-BZCAT Blazars

Based on the collected multiwavelength data, namely in the radio(NVSS, FIRST, RATAN-600), IR(WISE),optical(Pan-STARRS), UV(GALEX), and X-ray(ROSAT, Swift-XRT) ranges, we have performed a cluster analysis for the blazars of the Roma-BZCAT catalog. Using two machine learning methods, namely a combination of PCA with k-means clustering and Kohonen's self-organizing maps(SOMs), we have constructed an independent classification of the blazars(five classes) and compared the classes with the known Roma-BZCAT classification(FSRQs, BL Lacs, galaxy-dominated BL Lacs, and blazars of an uncertain type) as well as with the high synchrotron peaked(HSP) blazars from the 3HSP catalog and blazars from the TeVCat catalog. The obtained groups demonstrate concordance with the BL Lac/FSRQ classification along with a continuous character of the change in the properties. The group of HSP blazars stands out against the overall distribution. We examine the characteristics of the five groups and demonstrate distinctions in their spectral energy distribution shapes. The effectiveness of the clustering technique for objective analysis of multiparametric arrays of experimental data is demonstrated.

A Localization Method of High Energy Transients for All-sky Gamma-ray Monitor

Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up observations.Localization based on the relative counts of different detectors has been widely used for all-sky gamma-ray monitors.There are two major methods for this count distribution localization:χ^(2)minimization method and the Bayesian method.Here we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the χ^(2)method.With comprehensive simulations,we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than the χ^(2)method,especially for weak bursts.We further proposed a location-spectrum iteration approach based on the Bayesian inference,which could alleviate the problems caused by the spectral difference between the burst and location templates.Our method is very suitable for scenarios with limited computation resources or timesensitive applications,such as in-flight localization software,and low-latency localization for rapidly follow-up observations.

PSRDP:A Parallel Processing Method for Pulsar Baseband Data

To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRDP can perform operations such as baseband data unpacking,channel separation,coherent dedispersion,Stokes detection,phase and folding period prediction,and folding integration in GPU clusters.We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes,and the J0332+5434 pulsar baseband data generated by the self-developed backend of the Nan Shan Radio Telescope.We obtained the pulse profiles of each baseband data.Through experimental analysis,we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy(DSPSR),which verified the effectiveness of the PSRDP algorithm.Furthermore,using the same baseband data,we compared the processing speed of PSRDP with DSPSR,and the results showed that PSRDP was not slower than DSPSR in terms of speed.The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT(Qi Tai radio Telescope)ultra-wide bandwidth pulsar baseband data.

In-flight Energy Calibration of the GECAM Gamma-ray Detectors

The Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor(GECAM)mission is designed to monitor the Gamma-Ray Bursts(GRBs)associated with gravitational waves and other high-energy transient sources.The mission consists of two microsatellites which are planned to operate at the opposite sides of the Earth.Each GECAM satellite could detect and localize GRBs in about 8 keV-5 MeV with its 25 Gamma-Ray Detectors(GRDs).In this work,we report the in-flight energy calibration of GRDs using the characteristic gamma-ray lines in the background spectra,and show their performance evolution during the commissioning phase.Besides,a preliminary cross-calibration of energy response with Fermi GBM data is also presented,validating the energy response of GRDs.

Identifications of RR Lyrae Stars and Quasars from the Simulated Data of Mephisto-W Survey

We have investigated the feasibilities and accuracies of the identifications of RR Lyrae stars and quasars from the simulated data of the Multi-channel Photometric Survey Telescope(Mephisto)W Survey.Based on the variable sources light curve libraries from the Sloan Digital Sky Survey(SDSS)Stripe 82 data and the observation history simulation from the Mephisto-W Survey Scheduler,we have simulated the uvgriz multi-band light curves of RR Lyrae stars,quasars and other variable sources for the first year observation of Mephisto W Survey.We have applied the ensemble machine learning algorithm Random Forest Classifier(RFC)to identify RR Lyrae stars and quasars,respectively.We build training and test samples and extract~150 features from the simulated light curves and train two RFCs respectively for the RR Lyrae star and quasar classification.We find that,our RFCs are able to select the RR Lyrae stars and quasars with remarkably high precision and completeness,with purity=95.4%and completeness=96.9%for the RR Lyrae RFC and purity=91.4%and completeness=90.2%for the quasar RFC.We have also derived relative importances of the extracted features utilized to classify RR Lyrae stars and quasars.

GPU Accelerated Marine Data Visualization Method

The study of marine data visualization is of great value. Marine data, due to its large scale, random variation and multiresolution in nature, are hard to be visualized and analyzed. Nowadays, constructing an ocean model and visualizing model results have become some of the most important research topics of ‘Digital Ocean'. In this paper, a spherical ray casting method is developed to improve the traditional ray-casting algorithm and to make efficient use of GPUs. Aiming at the ocean current data, a 3D view-dependent line integral convolution method is used, in which the spatial frequency is adapted according to the distance from a camera. The study is based on a 3D virtual reality and visualization engine, namely the VV-Ocean. Some interactive operations are also provided to highlight the interesting structures and the characteristics of volumetric data. Finally, the marine data gathered in the East China Sea are displayed and analyzed. The results show that the method meets the requirements of real-time and interactive rendering.

The Data Processing of the LAMOST Medium-resolution Spectral Survey of Galactic Nebulae(LAMOST MRS-N Pipeline)

The Large sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) medium-resolution spectral survey of Galactic Nebulae(MRS-N) has conducted for more than three years since 2018 September and observed more than190 thousand nebular spectra and 20 thousand stellar spectra.However,there is not yet a data processing pipeline for nebular spectra.To significantly improve the accuracy of nebulae classification and their physical parameters,we developed the MRS-N Pipeline.This article presented in detail each data processing step of the MRS-N Pipeline,such as removing cosmic rays,merging single exposure,fitting sky light emission lines,wavelength recalibration,subtracting skylight,measuring nebular parameters,creating catalogs and packing spectra.Finally,a description of the data products,including nebular spectra files and parameter catalogs,is provided.

The first data release of LAMOST low-resolution single-epoch spectra

LAMOST Data Release 5,covering 17000 deg^(2) from-10°to 80°in declination,contains 9 million co-added low-resolution spectra of celestial objects,each spectrum combined from repeat exposure of two to tens of times during Oct 2011 to Jun 2017.In this paper,we present the spectra of individual exposures for all the objects in LAMOST Data Release 5.For each spectrum,the equivalent width of 60lines from 11 different elements are calculated with a new method combining the actual line core and fitted line wings.For stars earlier than F type,the Balmer lines are fitted with both emission and absorption profiles once two components are detected.Radial velocity of each individual exposure is measured by minimizing χ^(2) between the spectrum and its best template.The database for equivalent widths of spectral lines and radial velocities of individual spectra are available online.Radial velocity uncertainties with different stellar type and signal-to-noise ratio are quantified by comparing different exposure of the same objects.We notice that the radial velocity uncertainty depends on the time lag between observations.For stars observed in the same day and with signal-to-noise ratio higher than 20,the radial velocity uncertainty is below 5 km s^(-1),and increases to 10 km s^(-1) for stars observed in different nights.

A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

This paper proposes a two-step general framework for reversible data hiding(RDH)schemes with controllable contrast enhancement.The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity(EC),while the second step is used for increasing image contrast.In the second step,some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization(HE),which would lead to the image contrast enhancement.However,for HE,the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded.Therefore,in our proposed framework,contrast over-enhancement is avoided by controlling the degree of contrast enhancement.Since the second step can only provide a small amount of data due to controlled contrast enhancement,the first one helps to achieve a large amount of data without degrading visual quality.Any RDH method which can achieve high EC while preserve good visual quality,can be selected for the first step.In fact,Gao et al.’s method is a special case of our proposed framework.In addition,two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.

BGLS-based method of estimating the rotational periods of asteroids

As the asteroid rotational period is important to the study of the properties of asteroids(e.g.,super-fast rotators have structures owing an internal cohesion(rather than being rubble piles bounded by gravity only) so as not to fly apart), constructing an effective and fast method used to search the period attracts much researchers' attention. Recently, the Bayesian generalized Lomb–Scargle(BGLS)periodogram was developed to improve the convergence efficiency of the Lomb–Scargle method. However,the result of BGLS varies with the frequency range and cannot meet the two minimum/maximum requirements for a complete rotation of the asteroid. We propose a robust BGLS-based method that efficiently determines rotational periods. The proposed method employs a polynomial series to fit folded light curves with potential periods, initially calculated using the BGLS periodogram, and adopts a merit function to estimate and refine best-fit periods. We estimate the rotational periods of 30 asteroids applying the new method to light curves from the Palomar Transient Factory. Results confirm the effectiveness of the BGLS-based method in deriving rotational periods from ground-based observations of asteroids. Further application of the BGLS-based method to sparse light curves, such as Gaia data, is discussed.

Latitudinal migration of sunspots based on the ESAI database

The latitudinal migration of sunspots toward the equator,which implies there is propagation of the toroidal magnetic flux wave at the base of the solar convection zone,is one of the crucial observational bases for the solar dynamo to generate a magnetic field by shearing of the pre-existing poloidal magnetic field through differential rotation.The Extended time series of Solar Activity Indices（ESAI）elongated the Greenwich observation record of sunspots by several decades in the past.In this study,ESAI＇s yearly mean latitude of sunspots in the northern and southern hemispheres during the years 1854 to 1985 is utilized to statistically test whether hemispherical latitudinal migration of sunspots in a solar cycle is linear or nonlinear.It is found that a quadratic function is statistically significantly better at describing hemispherical latitudinal migration of sunspots in a solar cycle than a linear function.In addition,the latitude migration velocity of sunspots in a solar cycle decreases as the cycle progresses,providing a particular constraint for solar dynamo models.Indeed,the butterfly wing pattern with a faster latitudinal migration rate should present stronger solar activity with a shorter cycle period,and it is located at higher latitudinal position,giving evidence to support the Babcock-Leighton dynamo mechanism.

Systematic Review of Graphical Visual Methods in Honeypot Attack Data Analysis

Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations’ networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabilities. To effectively detect and mitigate cyberattacks, both computerized and visual analyses are typically required. However, most security analysts are not adequately trained in visualization principles and/or methods, which is required for effective visual perception of useful attack information hidden in attack data. Additionally, Honeypot has proven useful in cyberattack research, but no studies have comprehensively investigated visualization practices in the field. In this paper, we reviewed visualization practices and methods commonly used in the discovery and communication of attack patterns based on Honeypot network traffic data. Using the PRISMA methodology, we identified and screened 218 papers and evaluated only 37 papers having a high impact. Most Honeypot papers conducted summary statistics of Honeypot data based on static data metrics such as IP address, port, and packet size. They visually analyzed Honeypot attack data using simple graphical methods (such as line, bar, and pie charts) that tend to hide useful attack information. Furthermore, only a few papers conducted extended attack analysis, and commonly visualized attack data using scatter and linear plots. Papers rarely included simple yet sophisticated graphical methods, such as box plots and histograms, which allow for critical evaluation of analysis results. While a significant number of automated visualization tools have incorporated visualization standards by default, the construction of effective and expressive graphical methods for easy pattern discovery and explainable insights still requires applied knowledge and skill of visualization principles and tools, and occasionally, an interdisciplinary collaboration with peers. We, therefore, suggest the need, going forward, for non-classical graphical methods for visualizing attack patterns and communicating analysis results. We also recommend training investigators in visualization principles and standards for effective visual perception and presentation.

The influence of the observational strategies of pulsar timing on the properties of pulsar clocks

Pulsars are very stable spinning stars, which have the potential to application in the work of time-keeping and autonomous navigation in deep space. For time application, an individual pulsar can be regarded as a clock. The accuracy and stability of a pulsar clock are mainly determined by various timing noises and the measurement errors;however, they would be affected by the concrete observational strategy.Taking four millisecond pulsars from the first data released by International Pulsar Timing Array(IPTA) as an example, we investigated the influences of different observational strategies on the properties of pulsar clocks by removing some data in various ways. We find that the long-term stabilities of pulsar clocks are nearly not affected by increasing the observational cadence with a fixed time span. It is also found that the capabilities of prediction by pulsar clocks are also hardly affected by different observational strategies,which is reflected by both the stable weighted root-mean-square(wrms) and the stability of the resulting pre-fit timing residuals, unless the data span is too short or the data period is too far from the start of prediction.

Deep Learning Applications Based on WISE Infrared Data:Classification of Stars,Galaxies and Quasars

The Wide-field Infrared Survey Explorer(WISE)has detected hundreds of millions of sources over the entire sky.However,classifying them reliably is a great challenge due to degeneracies in WISE multicolor space and low detection levels in its two longest-wavelength bandpasses.In this paper,the deep learning classification network,IICnet(Infrared Image Classification network),is designed to classify sources from WISE images to achieve a more accurate classification goal.IICnet shows good ability on the feature extraction of the WISE sources.Experiments demonstrate that the classification results of IICnet are superior to some other methods;it has obtained 96.2%accuracy for galaxies,97.9%accuracy for quasars,and 96.4%accuracy for stars,and the Area Under Curve of the IICnet classifier can reach more than 99%.In addition,the superiority of IICnet in processing infrared images has been demonstrated in the comparisons with VGG16,GoogleNet,ResNet34,Mobile Net,EfficientNetV2,and RepVGG-fewer parameters and faster inference.The above proves that IICnet is an effective method to classify infrared sources.

The mini-GWAC optical follow-up of gravitational wave alerts – results from the O2 campaign and prospects for the upcoming O3 run

The second(O2)observational campaign of gravitational waves(GWs)organized by the LIGO/Virgo Collaborations has led to several breakthroughs such as the detection of GW signals from merger systems involving black holes or neutrons stars.During O2,14 GW alerts were sent to the astronomical community with sky regions mostly covering over hundreds of square degrees.Among them,six were finally confirmed as real astrophysical events.Since 2013,a new set of ground-based robotic telescopes called Ground-based Wide Angle Camera system(GWAC)project and its pathfinder mini-GWAC has been developed to contribute to the various challenges of multi-messenger and time domain astronomy.The GWAC system is built up in the framework of the ground-segment system of the SVOM mission that will be devoted to the study of the multi-wavelength transient sky in the next decade.During O2,only the mini-GWAC telescope network was fully operational.Due to the wide field of view and fast automatic follow-up capabilities of the mini-GWAC telescopes,they were adept to efficiently cover the sky localization areas of GW event candidates.In this paper,we present the mini-GWAC pipeline we have set up to respond to GW alerts and we report our optical follow-up observations of eight GW alerts detected during the O2 run.Our observations provided the largest coverage of the GW localization areas with a short latency made by any optical facility.We found tens of optical transient candidates in our images,but none of those could be securely associated with any confirmed black hole-black hole merger event.Based on this first experience and the near future technical improvements of our network system,we will be more competitive in detecting the optical counterparts from some GW events that will be identified during the upcoming O3 run,especially those emerging from binary neutron star mergers.

The FAST Galactic Plane Pulsar Snapshot Survey.II.Discovery of 76 Galactic Rotating Radio Transients and the Enigma of RRATs

We have carried out the Galactic Plane Pulsar Snapshot(GPPS)survey by using the Five-hundred-meter Aperture Spherical radio Telescope(FAST),the most sensitive systematic pulsar survey in the Galactic plane.In addition to more than 500 pulsars already discovered through normal periodical search,we report here the discovery of 76 new transient radio sources with sporadic strong pulses,detected by using the newly developed module for a sensitive single-pulse search.Their small DM values suggest that they all are Galactic rotating radio transients(RRATs).They show different properties in the follow-up observations.More radio pulses have been detected from 26 transient radio sources but no periods can be found due to a limited small number of pulses from all FAST observations.The followup observations show that 16 transient sources are newly identified as being the prototypes of RRATs with a period already determined from more detected sporadic pulses,and 10 sources are extremely nulling pulsars,and 24 sources are weak pulsars with sparse strong pulses.On the other hand,48 previously known RRATs have been detected by the FAST,either during verification observations for the GPPS survey or through targeted observations of applied normal FAST projects.Except for one RRAT with four pulses detected in a session of 5-minute observation and four RRATs with only one pulse detected in a session,sensitive FAST observations reveal that 43 RRATs are just generally weak pulsars with sporadic strong pulses or simply very nulling pulsars,so that the previously known RRATs always have an extreme emission state together with a normal hardly detectable weak emission state.This is echoed by the two normal pulsars J1938+2213 and J1946+1449 with occasional brightening pulses.Though strong pulses of RRATs are very outstanding in the energy distribution,their polarization angle variations follow the polarization angle curve of the averaged normal pulse profile,suggesting that the predominant sparse pulses of RRATs are emitted in the same region with the same geometry as normal weak pulsars.

A GPU based single-pulse search pipeline(GSP)with database and its application to the Commensal Radio Astronomy FAST Survey(CRAFTS)

We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database.We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey(CRAFTS),which resulted in quasi-real-time processing.The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients(RRATs)and fast radio bursts(FRBs).We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band(UWB)receiver.GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB.GSP also discovered 13 new pulsars.We measured the computational efficiency of GSP to be~120 times faster than the original PRESTO and~60 times faster than an MPI-parallelized version of PRESTO.