Dynamic Analysis Tools Research Articles

Artificial dissipation model applied to Euler equations for analysis of supersonic flow around a geometric configurations ramp and diffusor type

Very High Temperature Gas Cooled Reactors - VHTGRs are studied by several research groups for the development of advanced reactors that can meet the world's growing energy demand. The analysis of the flow of helium coolant around the various geometries at the core of these reactors through computational fluid dynamics techniques is an essential tool in the development of conceptual designs of nuclear power plants that provide added security. This analysis suggests a close analogy with aeronautical cases widely studied using computational numerical techniques to solve systems of governing equations for the flow involved. The present work consists in using the DISSIPA2D_EULER code, to solve the Euler equations in a conservative form, in two-dimensional space employing a finite difference formulation for spatial discretization using the Euler method for explicit marching in time. The physical problem of supersonic flow of helium gas along a ramp and diffusor configurations is considered. For this, the Jameson and Mavriplis algorithm and the linear artificial dissipation model of Pulliam was implemented. A spatially variable time step is employed aiming to accelerate the convergence to the steady state solution. The main purpose of this work is obtain computational tools for flow analysis through the study the cited dissipation model and describe their characteristics in relation to the overall quality of the solution, as well as obtain preliminary results for the development of computational tools of dynamic analysis of helium gas flow in gas-cooled reactors.

Hyers–Ulam stability and existence of solution for hybrid fractional differential equation with p-Laplacian operator

This manuscript studies the hybrid fractional differential equations (FDEs) with the p-Laplacian operator. The main aim of this research work is to establish the existence and uniqueness(EU) results as well as to analyze the Hyers-Ulam (HU) stability for hybrid FDEs involving fractional derivatives of various orders with the p-Laplacian operator. We will convert the given problem into an equivalent integral form of hybrid FDEs for EU results with the help of the green function. The existence of solution(ES) is investigated using a fixed point theorem, and the uniqueness of the solution is obtained using the Banach contraction mapping principle technique. The dynamical systems and functional analysis tools are applied to analyze the HU stability result. An example is given to demonstrate our obtained results.

An approach to dynamic malware analysis based on system and application code split

This paper discusses the development of tools for dynamic malware analysis. The main idea is to provide total control on a suspicious sample execution on the test computer. The approach we propose is to separate the application code from the system code by using memory pages access control. Thus, we are able to detect all system API calls and non-standard ways to transfer the control flow. Our tools (codename ToolChain) intentionally consist of a Control module, a Scheduling module, and a Cloaking module. In this paper, we focus mainly on the Control module. We monitor internal target process events by using invasive methods such as a system call hook or an executable file patch. This research describes the key creation stages of the prototype, with the basic functionality and technical ideas on handling several issues, such as analysis of multi-threaded applications, cloaking of the presence of analytical tools, and mitigation of the performance degradation of the operation system.

MalView: Interactive Visual Analytics for Comprehending Malware Behavior

Malicious applications are usually comprehended through two major techniques, namely static and dynamic analyses. Through static analysis, a given malicious program is parsed, and some representative artifacts (e.g., control-flow graphs) are produced without any execution; whereas, the given malicious application needs to be executed when conducting dynamic analysis. These two mainstream techniques for analyzing the given software are effective in detecting certain classes of malware. More specifically, through static analysis, the patterns and signature of the malware are exposed, helping in detecting any known malicious payload hidden in or injected into the code. On the other hand, behavioral and run-time execution patterns of software are explored through dynamic analysis. To ease the analysis process, a third analysis approach, known as the visual representation of the artifacts created by both static and dynamic analysis tools, would also be a supplementary asset for malware experts. This paper introduces “ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MalView</i> ”, an interactive visualization platform, for malware analysis by which pattern matching techniques on both signature-based and behavioral analysis artifacts can be utilized to 1) classify malware, 2) identify the intention and location of the malicious payload in the artifacts, 3) analyze unknown malware (i.e., zero-day malware) by recognizing any unusual signature or behavior, and 4) explore the time dependencies and thus the system components affected or tampered by the underlying malware. The results of several case studies conducted in this work show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MalView</i> offers more features and information compared to some other visualization tools, facilitating the malware analysis process.

Ethereum Smart Contract Analysis Tools: A Systematic Review

Blockchain technology and its applications are gaining popularity day by day. It is a ground-breaking technology that allows users to communicate without the need of a trusted middleman. A smart contract (self-executable code) is deployed on the blockchain and auto executes due to a triggering condition. In a no-trust contracting environment, smart contracts can establish trust among parties. Terms and conditions embedded in smart contracts will be imposed immediately when specified criteria have been fulfilled. Due to this, the malicious assailants have a special interest in smart contracts. Blockchains are immutable means if some transaction is deployed or recorded on the blockchain, it becomes unalterable. Thus, smart contracts must be analyzed to ensure zero security vulnerabilities or flaws before deploying the same on the blockchain because a single vulnerability can lead to the loss of millions. For analyzing the security vulnerabilities of smart contracts, various analysis tools have been developed to create safe and secure smart contracts. This paper presents a systematic review on Ethereum smart contracts analysis tools. Initially, these tools are categorized into static and dynamic analysis tools. Thereafter, different sources code analysis techniques are studied such as taint analysis, symbolic execution, and fuzzing techniques. In total, 86 security analysis tools developed for Ethereum blockchain smart contract are analyzed regardless of tool type and analysis approach. Finally, the paper highlights some challenges and future recommendations in the field of Ethereum smart contracts.

Challenges in computational fluid dynamics applications for bone tissue engineering.

Bone injuries or defects that require invasive surgical treatment are a serious clinical issue, particularly when it comes to treatment success and effectiveness. Accordingly, bone tissue engineering (BTE) has been researching the use of computational fluid dynamics (CFD) analysis tools to assist in designing optimal scaffolds that better promote bone growth and repair. This paper aims to offer a comprehensive review of recent studies that use CFD analysis in BTE. The mechanical and fluidic properties of a given scaffold are coupled to each other via the scaffold architecture, meaning an optimization of one may negatively affect the other. For example, designs that improve scaffold permeability normally result in a decreased average wall shear stress. Linked with these findings, it appears there are very few studies in this area that state a specific application for their scaffolds and those that do are focused on in vitro bioreactor environments. Finally, this review also demonstrates a scarcity of studies that combine CFD with optimization methods to improve scaffold design. This highlights an important direction of research for the development of the next generation of BTE scaffolds.

IRlab - Platform for thermal video analysis in evaluation of peripheral thermal behavior and blood perfusion

Background and objectivesDynamic thermal imaging in medicine has several advantages in comparison to static thermal image analysis and has potential as a novel patient assessment method e.g. in the area of vascular surgery. Since dynamic thermal imaging has become in the scope of research only during the last decade, the computational available analysis methods are often lacking or not existing. Most of the published software is not available to the research community or are behind a paywall. IRlab provides an easy-to-use dynamic thermal video processing and analysis platform, freely accessible to researchers. MethodsIRlab is programmed in Matlab R2020b. Computational tools for dynamic analysis are divided into spatio-temporal and spectral methods, where spatio-temporal methods consist of region of interest delineation tools, thermal modulation analysis, standard thermal measures such as median, maximum, minimum and deviation values, and subtraction and gamma maps. Spectral methods include spectral band power, spectral flow, and wavelet analysis tools. Preliminary data of a single healthy subject was analyzed with the program as a sample run. ResultsIRlab provides a platform for lower limb thermal image and video analysis with a clear workflow and variety of processing and analysis tools for time and frequency space analysis. The whole source code for IRlab is freely available for the research community under the General public license. ConclusionsIRlab is a versatile tool for dynamic thermal image and video processing. Freeware and open-source programs for medical thermal imaging are severely lacking, thus as a completely open-source project IRlab offers a unique platform for researchers within the field of medical thermal imaging.

Инструмент динамического анализа IoT-систем ELF с поддержкой символьных вычислений

As a result of background work on analysis in embedded Linux OS, the authors created the ELF (embedded linux fuzzing) tool that provides functionality for use in conventional dynamic analysis tools working with IoT devices. The article discusses the use of full-system symbolic execution for the analysis of IoT systems based on Linux kernels, describes how to integrate S2E full-system symbolic execution frameworks into the ELF tool environment, as well as the possibility of applicability of the resulting toolchain to the implementation of distributed hybrid IoT fuzzing.

Dynamic Simulation and Thermoeconomic Analysis of a Hybrid Renewable System Based on PV and Fuel Cell Coupled with Hydrogen Storage

The production of “green hydrogen” is currently one of the hottest topics in the field of renewable energy systems research. Hydrogen storage is also becoming more and more attractive as a flexible solution to mitigate the power fluctuations of solar energy systems. The most promising technology for electricity-to-hydrogen conversion, and vice versa, is the reversible solid-oxide cell (SOC). This device is still very expensive, but it exhibits excellent performance under dynamic operating conditions compared to the competing devices. This work presents the dynamic simulation of a prototypal renewable plant combining a 50 kW photovoltaic (PV) field with a 50 kW solid-oxide electrolyzer cell (SOEC) and a compressed hydrogen tank. The electricity is used to meet the energy demand of a dwelling located in the area of Campi Flegrei (Naples). The SOC efficiency is simulated by developing a mathematical model in MATLAB®. The model also calculates the cell operating temperature as a function of the input current. Once the optimal values of the operating parameters of the SOC are calculated, the model is integrated in the transient system simulation tool (TRNSYS) for dynamic analysis. Furthermore, this work presents a parametric analysis of the hydrogen storage system (HSS). The results of the energy and environmental analyses show that the proposed system can reach a primary energy saving by 70% and an amount of saved CO2 of 28 tons/year. Some possible future market scenarios are considered for the economic analysis. In the most realistic case, the optimal configuration shows a simple pay back lower than 10 years and a profit index of 46%.

A General Reconstruction Method for Multidimensional Sparse Sampling Nuclear Magnetic Resonance Spectroscopy.

Multidimensional NMR spectroscopy provides a powerful tool for structure elucidation and dynamic analysis of complex samples, particularly for biological macromolecules. Multidimensional sparse sampling effectively accelerates NMR experiments while an efficient reconstruction method is generally required for unraveling spectra. Various reconstruction methods were proposed for pure Fourier NMR (only involving chemical shifts and J couplings detection). However, reconstruction concerned with Laplace-related NMR (i.e., involving relaxation or diffusion detection) is more challenging due to its ill-posed property. The existing Laplace-related NMR sparse sampling reconstruction methods suffer from poor resolution and possible artifacts in the resulting spectra owing to the pitfalls of the optimization algorithms. Herein, we propose a general approach for fast high-resolution reconstruction of multidimensional sparse sampling NMR, including pure Fourier, mixed Fourier-Laplace, and pure Laplace NMR, benefiting from the comprehensive sparse constraint and effective optimization algorithm and thus showing the promising prospects of multidimensional NMR.

Cinema:Snap: Real-time tools for analysis of dynamic diamond anvil cell experiment data.

We developed tools and a workflow for real-time analysis of data from dynamic diamond anvil cell experiments performed at user light sources. These tools allow users to determine the phases of matter observed during the compression of materials in order to make decisions during an experiment to improve the quality of experimental results and maximize the use of scarce experimental facility time. The tools fill a gap in dynamic compression data analysis tools that are real-time, are flexible to the needs of high-pressure scientists, connect to automated processing of results, can be easily incorporated into workflows with existing tools and data formats, and support remote experimental data analysis workflows. Specific analytics developed include novel automated two-peak analysis for overlapping peaks and multiple phases, coordinated views of pressure and temperature values, full-compression contour plots, and configurable views of integrated x-ray diffraction. We present an experimental use case to show how the tools produce real-time analytics that help the scientists revise parameters for the next compression.

Exploring the use of static and dynamic analysis to improve the performance of the mining sandbox approach for android malware identification

The popularization of the Android platform and the growing number of Android applications (apps) that manage sensitive data turned the Android ecosystem into an attractive target for malicious software. For this reason, researchers and practitioners have investigated new approaches to address Android’s security issues, including techniques that leverage dynamic analysis to mine Android sandboxes. The mining sandbox approach consists in running dynamic analysis tools on a benign version of an Android app. This exploratory phase records all calls to sensitive APIs. Later, we can use this information to (a) prevent calls to other sensitive APIs (those not recorded in the exploratory phase) or (b) run the dynamic analysis tools again in a different version of the app. During this second execution of the fuzzing tools, a warning of possible malicious behavior is raised whenever the new version of the app calls a sensitive API not recorded in the exploratory phase.The use of a mining sandbox approach is an effective technique for Android malware analysis, as previous research works revealed. Particularly, existing reports present an accuracy of almost 70% in the identification of malicious behavior using dynamic analysis tools to mine android sandboxes. However, although the use of dynamic analysis for mining Android sandboxes has been investigated before, little is known about the potential benefits of combining static analysis with a mining sandbox approach for identifying malicious behavior. Accordingly, in this paper we present the results of two studies that investigate the impact of using static analysis to complement the performance of existing dynamic analysis tools tailored for mining Android sandboxes, in the task of identifying malicious behavior.In the first study we conduct a non-exact replication of a previous study (hereafter BLL-Study) that compares the performance of test case generation tools for mining Android sandboxes. Differently from the original work, here we isolate the effect of an independent static analysis component (DroidFax) they used to instrument the Android apps in their experiments. This decision was motivated by the fact that DroidFax could have influenced the efficacy of the dynamic analyses tools positively—through the execution of specific static analysis algorithms DroidFax also implements. In our second study, we carried out a new experiment to investigate the efficacy of taint analysis algorithms to complement the mining sandbox approach previously used to identify malicious behavior. To this end, we executed the FlowDroid tool to mine the source–sink flows from benign/malign pairs of Android apps used in a previous research work.Our study brings several findings. For instance, the first study reveals that DroidFax alone (static analysis) can detect 43.75% of the malwares in the BLL-Study dataset, contributing substantially in the performance of the dynamic analysis tools in the BLL-Study. The results of the second study show that taint analysis is also practical to complement the mining sandboxes approach, with a performance similar to that reached by dynamic analysis tools.

On the efficacy and accuracy of freezing technique for the response analysis of time-varying vehicle-bridge interaction systems

The basic problem of vehicle-bridge interaction (VBI) is a linear time-varying system for which no exact solution is available and even numerical solutions can be complicated. In this paper, the efficacy and accuracy of a freezing technique (FT), in which the time parameter is frozen, applied to obtain the forced response of the VBI system are assessed. To improve the accuracy, a time-step approach, in which FT is employed in each time subinterval, is proposed. The FT is relatively simple to implement and results are validated with and compared to those obtained by a highly accurate Runge-Kutta method (treated as “exact” solution) for different vehicle models, vehicle and bridge parameters, and time steps. It is found that numerical results obtained by the FT are accurate, even for high vehicle speeds. Moreover, the FT outperforms the Newmark-β method. An analytical local error bound for the FT is derived, which shows the error dependence on the vehicle-bridge coupling dynamics, in particular, the tire stiffness and the vehicle speed. An important implication of this study is that, since the FT can be applied to analyze the time-varying VBI system, the method essentially transforms the coupled system into a time sequence of linear time-invariant (LTI) systems and allows tools for dynamic analysis and controller design of LTI systems to be applicable to the VBI problem.

Changes in the Structures and Directions of Rock Excavation Research from 1999 to 2020: A Bibliometric Study

Rock excavation has been the hot spot and frontier of scientific research. Rock excavation research is in a period of rapid development. The bibliographies included in ISI Web of Knowledge database from 1999–2020 were used as data samples, and the collected data were analyzed by literature co-citation and cluster analysis using CiteSpace and VOSviewer information visualization techniques and dynamic network analysis tools. A knowledge map of the evolution of bibliometric research development is drawn to reveal the representative literature in the field of bibliometrics. The hot areas of bibliometric research are introduced. The development trend of bibliometrics is proposed. The results of the study show that the amount of the literature on rock excavation is growing rapidly. A large amount of the foreign literature is available in China, the United States, Australia, Canada, France, and other countries. The main included journals are Tunnelling and Underground Space Technology, International Journal of Rock Mechanics and Mining Sciences, “Rock Mechanics and Rock Engineering,” “Engineering Geology,” and “Bulletin of Engineering Geology and the Environment.” Keyword co-occurrence analysis includes the following contents: rock damage constitutive model, excavation damage area, numerical simulation, stability analysis support, and prediction technology of rock.

HAMBug: A Hybrid CPU-FPGA System to Detect Race Conditions

The evolution of computer algorithms and micro-architectures continuously leads to novel applications and solutions that explore modern computers' potential. A drawback of this development is the rising complexity of hardware-oriented tests during software development. This brief proposes Hambug, a method to support developers during software testing of parallel applications in CPU-FPGA environments. The main component is a run-time memory analyzer that employs shared channels. Thus, Hambug enables memory analysis of parallel applications without influencing the CPU using a hardware-based debug module. Experimental results indicate that this method presents lower slowdown compared with modern dynamic analysis tools.

Isonormal surfaces: A new tool for the multidimensional dynamical analysis of iterative methods for solving nonlinear systems

The dynamical behavior of the rational vectorial operator associated with a multidimensional iterative method on polynomial systems gives us interesting information about the stability of the iterative scheme. The stability of fixed points, dynamic planes, bifurcation diagrams, etc. are known tools that provide us this information. In this manuscript, we introduce a new tool, which we call isonormal surface, to complement the information about the stability of the iterative method provided by the dynamical elements mentioned above. These dynamical instruments are used for analyzing the stability of a parametric family of multidimensional iterative schemes in terms of the value of the parameter. Some numerical tests confirm the obtained dynamical results.

Interactive Visual Graph Analytics on the Web

We present a web-based network visual analytics platform called GraphVis that combines interactive visualizations with analytic techniques to reveal important patterns and insights for sense making, reasoning, and decision-making. The platform is designed with simplicity in mind and allows users to visualize and explore networks in seconds with a simple drag-and-drop of a graph file into the web browser. GraphVis is fast and flexible, web-based, requires no installation, while supporting a wide range of graph formats as well as state-of-the-art visualization and analytic techniques. In particular, the multi-level network analysis engine of GraphVis gives rise to a variety of new possibilities for exploring, analyzing, and understanding complex networks interactively in real-time. Finally, we also highlight other key aspects including filtering, querying, ranking, manipulating, exporting, partitioning (community/role discovery), as well as tools for dynamic network analysis and visualization, interactive graph generators (including two new block model approaches), and a variety of multi-level network analysis and statistical techniques.

Characteristics of inherent coupling structure of model climates

AbstractThis work proposes a framework to examine interactions of climate modes that are identified as leading EOF modes; their coupling structure is unveiled through correlation analysis and helps constructing a regression model, whose performance is compared across GCMs, thereby providing a quantitative overview of model performances in simulating mode-interaction. As demonstration surface temperature is analyzed for five CMIP5 PiControl simulations. Along with the seasonal land and ocean modes, four interannual modes are identified: Tropical Mode (TM) associated with the Hadley circulation, Tropical Pacific Mode (TPM) characterizing a zonal temperature contrast between the eastern tropical Pacific and the Atlantic-Indian ocean, and two annular modes: Arctic Mode (AM) and Ant-arctic Mode (AAM). All GCMs converge on the following: 1) TM strongly couples with seasonal signals of the previous year; 2) TPM leads TM by 1 year, thus a weaker zonal temperature contrast in the tropics contributes to warming in the entire tropical band one year later; 3) AM weakly couples to TM at a one-year lead, suggesting a colder north pole may contribute to colder tropics. In addition, all GCMs do not support a linear coupling between AAM and TM. The above-learned coupling structure is incorporated to construct an optimum regression model that demonstrates considerable predictive power. The proposed approach may both serve as a useful tool for dynamical analysis and lend insight into GCM differences. Its merit is demonstrated by the finding that different representations of the mean seasonal cycle in GCMs may account for the GCM-dependence of relative contributions of seasonal and inter-annual modes to TM variability.

Hypervisor-assisted dynamic malware analysis

Malware analysis is a task of utmost importance in cyber-security. Two approaches exist for malware analysis: static and dynamic. Modern malware uses an abundance of techniques to evade both dynamic and static analysis tools. Current dynamic analysis solutions either make modifications to the running malware or use a higher privilege component that does the actual analysis. The former can be easily detected by sophisticated malware while the latter often induces a significant performance overhead. We propose a method that performs malware analysis within the context of the OS itself. Furthermore, the analysis component is camouflaged by a hypervisor, which makes it completely transparent to the running OS and its applications. The evaluation of the system’s efficiency suggests that the induced performance overhead is negligible.

Extending Science from Lunar Laser Ranging

The Lunar Laser Ranging (LLR) experiment has accumulated 50 years of range data of improving accuracy from ground stations to the laser retroreflector arrays (LRAs) on the lunar surface. The upcoming decade offers several opportunities to break new ground in data precision through the deployment of the next generation of single corner-cube lunar retroreflectors and active laser transponders. This is likely to expand the LLR station network. Lunar dynamical models and analysis tools have the potential to improve and fully exploit the long temporal baseline and precision allowed by millimetric LLR data. Some of the model limitations are outlined for future efforts. Differential observation techniques will help mitigate some of the primary limiting factors and reach unprecedented accuracy. Such observations and techniques may enable the detection of several subtle signatures required to understand the dynamics of the Earth-Moon system and the deep lunar interior. LLR model improvements would impact multi-disciplinary fields that include lunar and planetary science, Earth science, fundamental physics, celestial mechanics and ephemerides.