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.

An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results

An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a mi- crowave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea sur- face is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments （MoM）, and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an off-spilled sea surface caused by the Hebei （Hebei province, China） Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different inci- dence angles on the backscattering coefficients.

DVL/RPM Based Velocity Filter Aiding in the Underwater Vehicle Integrated Inertial Navigation System

The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment.

A Systematic Molecular Dynamics Investigation on the Graphene Polymer Nanocomposites for Bulletproofing

In modern physics and fabrication technology,simulation of projectile and target collision is vital to improve design in some critical applications,like;bulletproofing and medical applications.Graphene,the most prominent member of two dimensional materials presents ultrahigh tensile strength and stiffness.Moreover,polydimethylsiloxane(PDMS)is one of the most important elastomeric materials with a high extensive application area,ranging from medical,fabric,and interface material.In this work we considered graphene/PDMS structures to explore the bullet resistance of resulting nanocomposites.To this aim,extensive molecular dynamic simulations were carried out to identify the penetration of bullet through the graphene and PDMS composite structures.In this paper,we simulate the impact of a diamond bullet with different velocities on the composites made of single-or bi-layer graphene placed in different positions of PDMS polymers.The underlying mechanism concerning how the PDMS improves the resistance of graphene against impact loading is discussed.We discuss that with the same content of graphene,placing the graphene in between the PDMS result in enhanced bullet resistance.This work comparatively examines the enhancement in design of polymer nanocomposites to improve their bulletproofing response and the obtained results may serve as valuable guide for future experimental and theoretical studies.

Ultra-stable and tough bioinspired crack-based tactile sensor for small legged robots

For legged robots,collecting tactile information is essential for stable posture and efficient gait.However,mounting sensors on small robots weighing less than 1 kg remain challenges in terms of the sensor’s durability,flexibility,sensitivity,and size.Crackbased sensors featuring ultra-sensitivity,small-size,and flexibility could be a promising candidate,but performance degradation due to crack growing by repeated use is a stumbling block.This paper presents an ultra-stable and tough bio-inspired crack-based sensor by controlling the crack depth using silver nanowire(Ag NW)mesh as a crack stop layer.The Ag NW mesh inspired by skin collagen structure effectively mitigated crack propagation.The sensor was very thin,lightweight,sensitive,and ultra-durable that maintains its sensitivity during 200,000 cycles of 0.5%strain.We demonstrate sensor’s feasibility by implementing the tactile sensation to bio-inspired robots,and propose statistical and deep learning-based analysis methods which successfully distinguished terrain type.

Biologically inspired ultrathin arrayed camera for high-contrast and high-resolution imaging

Compound eyes found in insects provide intriguing sources of biological inspiration for miniaturised imaging systems.Here,we report an ultrathin arrayed camera inspired by insect eye structures for high-contrast and super-resolution imaging.The ultrathin camera features micro-optical elements(MOEs),i.e.,inverted microlenses,multilayered pinhole arrays,and gap spacers on an image sensor.The MOE was fabricated by using repeated photolithography and thermal reflow.The fully packaged camera shows a total track length of 740μm and a field-of-view(FOV)of 73°.The experimental results demonstrate that the multilayered pinhole of the MOE allows high-contrast imaging by eliminating the optical crosstalk between microlenses.The integral image reconstructed from array images clearly increases the modulation transfer function(MTF)by~1.57 times compared to that of a single channel image in the ultrathin camera.This ultrathin arrayed camera provides a novel and practical direction for diverse mobile,surveillance or medical applications.