Network Traffic Synthesis and Simulation Framework for Cybersecurity Exercise Systems

In the rapidly evolving field of cybersecurity,the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly critical.Traditional methods often fall short in capturing the dynamic and complex nature of modern cyber threats.To address this gap,we propose a comprehensive framework designed to create authentic network environments tailored for cybersecurity exercise systems.Our framework leverages advanced simulation techniques to generate scenarios that mirror actual network conditions faced by professionals in the field.The cornerstone of our approach is the use of a conditional tabular generative adversarial network(CTGAN),a sophisticated tool that synthesizes realistic synthetic network traffic by learning fromreal data patterns.This technology allows us to handle technical components and sensitive information with high fidelity,ensuring that the synthetic data maintains statistical characteristics similar to those observed in real network environments.By meticulously analyzing the data collected from various network layers and translating these into structured tabular formats,our framework can generate network traffic that closely resembles that found in actual scenarios.An integral part of our process involves deploying this synthetic data within a simulated network environment,structured on software-defined networking(SDN)principles,to test and refine the traffic patterns.This simulation not only facilitates a direct comparison between the synthetic and real traffic but also enables us to identify discrepancies and refine the accuracy of our simulations.Our initial findings indicate an error rate of approximately 29.28%between the synthetic and real traffic data,highlighting areas for further improvement and adjustment.By providing a diverse array of network scenarios through our framework,we aim to enhance the exercise systems used by cybersecurity professionals.This not only improves their ability to respond to actual cyber threats but also ensures that the exercise is cost-effective and efficient.

Electrochemical partial reduction of Ni(OH)_(2) to Ni(OH)_(2)/Ni via coupled oxidation of an interfacing NiAl intermetallic compound for robust hydrogen evolution

Ni-based porous electrocatalysts have been widely used in the hydrogen evolution reaction(HER)in alkaline water electrolysis,and the catalysts are produced by selective leaching of Al from Ni-Al alloys.It is well known that chemical leaching of Ni-Al intermetallic compound(IMC)generates a high surface area in Ni(OH)_(2).However,the Ni(OH)_(2) produced by leaching the Ni-Al intermetallic compound retards the hydrogen evolution reaction,which is attributed to its weak hydrogen adsorption energy.In this study,we controlled the chemical state of Ni using plasma vapor deposition(PVD)followed by heat treatment,selective Al leaching,and electrochemical reduction.X-ray diffraction(XRD),scanning microscopy(SEM),transmission electron microscopy(TEM),and energy-dispersive X-ray spectroscopy(EDS)were used to confirm the phase evolution of the electrocatalysts during fabrication.We reveal that the heat-treated Ni-Al alloy with a thick Ni2Al3surface layer underwent selective Al leaching and produced biphasic interfaces comprising Ni(OH)_(2) and NiAl IMCs at the edges of the grains in the outermost surface layer.Coupled oxidation of the interfacing NiAl IMCs facilitated the partial reduction of Ni(OH)_(2) to Ni(OH)_(2)/Ni in the grains during electrochemical reduction,as confirmed by X-ray photoelectron spectroscopy(XPS).An electrocatalyst containing partially reduced Ni(OH)_(2)/Ni exhibited an overpotential of 54 mV at 10 mA/cm^(2) in a half-cell measurement,and a cell voltage of 1.675 V at 0.4 A/cm2for single-cell operation.A combined experimental and theoretical study(density functional theory calculations)revealed that the superior HER activity was attributed to the presence of partially reduced metallic Ni with various defects and residual Al,which facilitated water adsorption,dissociation,and finally hydrogen evolution.

论韩国技术竞争情报的发展及其在企业中的应用

在全面总结韩国技术竞争情报(CTI)服务的兴起及发展历史的基础上,客观分析了其CTI应用的特点及其效果,并且对韩国企业开展CTI活动的动力因素及其影响进行了深入研究。

论韩国技术竞争情报发展的现状、特点与动力

本文在全面总结韩国技术竞争情报(CTI)服务的兴起及发展现状的基础上,系统客观地分析了其CTI发展的特点及其效果,然后对韩国开展CTI活动的动力及其影响因素进行了初步研究。

论后发国家的企业技术竞争情报:战略与特征——以韩国三星电子的技术竞争情报发展模式为例

应用国际上通行的解释性案例分析方法,通过对韩国三星电子公司开展技术竞争情报活动的发展历程及其成功经验和教训进行深入剖析,揭示了后发国家企业技术竞争情报活动的发展规律和特殊性,认为后发国家企业技术竞争情报活动在目标动机、运行模式和信息来源等方面与发达国家相比存在着很大的差异,应当依据其特殊性与要求来指导和推动后发国家企业的技术竞争情报健康发展。

亚洲“四小龙”的竞争情报发展现状与特征分析

在总结亚洲"四小龙"竞争情报研究与服务兴起以及发展态势的基础上,深入分析了这些国家和地区竞争情报服务产业化发展的特征及效果,并就"四小龙"竞争情报服务业发展取得的成功经验及其给我们的启示进行了讨论。

A 3.3 kV 4H-SiC split gate MOSFET with a central implant region for superior trade-off between static and switching performance

A split gate MOSFET(SG-MOSFET)is widely known for reducing the reverse transfer capacitance(C_(RSS)).In a 3.3 kV class,the SG-MOSFET does not provide reliable operation due to the high gate oxide electric field.In addition to the poor static performance,the SG-MOSFET has issues such as the punch through and drain-induced barrier lowering(DIBL)caused by the high gate oxide electric field.As such,a 3.3 kV 4 H-SiC split gate MOSFET with a grounded central implant region(SG-CIMOSFET)is proposed to resolve these issues and for achieving a superior trade-off between the static and switching performance.The SG-CIMOSFET has a significantly low on-resistance(R_(ON))and maximum gate oxide field(E_(OX))due to the central implant region.A grounded central implant region significantly reduces the C_(RSS)and gate drain charge(Q_(GD))by partially screening the gate-to-drain capacitive coupling.Compared to a planar MOSFET,the SG MOSFET,central implant MOSFET(CIMOSFET),the SGCIMOSFET improve the R_(ON)×Q_(GD)by 83.7%,72.4%and 44.5%,respectively.The results show that the device features not only the smallest switching energy loss but also the fastest switching time.

3.3 kV 4H-SiC DMOSFET with a source-contacted dummy gate for high-frequency applications

In this paper,a 4 H-Si C DMOSFET with a source-contacted dummy gate(DG-MOSFET)is proposed and analyzed through Sentaurus TCAD and PSIM simulations.The source-contacted MOS structure forms fewer depletion regions than the PN junction.Therefore,the overlapping region between the gate and the drain can be significantly reduced while limiting RON degradation.As a result,the DG-MOSFET offers an improved high-frequency figure of merit(HF-FOM)over the conventional DMOSFET(C-MOSFET)and central-implant MOSFET(CI-MOSFET).The HF-FOM(RON×QGD)of the DG-MOSFET was improved by59.2%and 22.2%compared with those of the C-MOSFET and CI-MOSFET,respectively.In a double-pulse test,the DG-MOSFET could save total power losses of 53.4%and 5.51%,respectively.Moreover,in a power circuit simulation,the switching power loss was reduced by 61.9%and 12.7%in a buck converter and 61%and 9.6%in a boost converter.

Measurement of ^(59)Co(ai,x)reaction cross sections with the fast neutrons based on the ^(9)Be(p,n)reaction

The cross sections of the ^(59)Co(n,x)reaction in the average energy range of 15.2-37.2 MeV were meas-ured using activation and an off-line γ-ray spectrometric technique.The neutrons were generated from the ^(9)Be(p,n)reaction with proton beam energies of 25-45 MeV at the MC-50 Cyclotron facility of the Korean Institute of Radi-ological and Medical Sciences(KIRAMS).Theoretical cal lculations of neutron-induced reactions on ^(59)Co were per-formed using the nuclear model code TALYS-1.9.The results for the ^(59)Co(n,x)reactions were compared with the theoretical values obtained using TALYS-1.9 and the literature data provided in EXFOR and the TENDL 2019 nuc-lear data library.The theoretical values obtained using TALYS-1.9 with adjusted parameters are comparable to the experimental data.The measured reaction cross sections of a few radionuclides are new,and the others are compar-able to the literature data,and thus,they can strengthen the database.The present study on cross sections leads to useful insight into the mechanisms of ^(59)Co(n,x)reactions.