Nowadays, Malware propagation has become a major threat in cyber space. modeling Malware propagation process allows us to get a better understanding of the dynamics of Malware spreading as well as helping us to find effective defense mechanisms. Due to the security concerns, software diversity has re-ceived much attention as a cyber-defense mechanism. In this paper, considering software diversity approach, an epidemic model of Malware propagation in scale-free networks is proposed. Software diversi-ty as a defense mechanism reduces the Malware propagation process in the network. Simulation results show the effect of different parameters on the Malware propagation process. Also, we demonstrate that the assignment of diverse software packages to network nodes reduces the basic reproductive ratio and mal-ware propagation speed in the network. Moreover, the effect of weight's exponent on the speed of Malware propagation is investigated.

Scale-free network (SFN) is a conceptual model for online social networks and peer-to-peer networks, which exhibit a power-law degree distribution. Due to these characteristics, these networks are more vulnerable to the spread of Malware (such as virus and worm). modeling and simulation methods are used to evaluate the propagation behavior of Malware in scale-free networks and analyze the defense strategies against Malware propagation. To do so, a high number of events should be processed and details of network nodes should be considered. This makes the existing discrete-event simulation methods inappropriate for running on large and complex networks. Hence, for modeling the propagation behavior of Malware, fluid models, which need not know the details of network, seems to be more appropriate. In this paper, for fluid simulation of Malware propagation, a scale-free network is conceptually represented as a backbone network including supernodes, any one of which includes several nodes of the network. Each supernode in the case of infection can propagate pollution as a fluid flow to its neighboring nodes. Therefore, the main process of Malware propagation can be modeled without considering the details of every node. To evaluate the proposed method, an agent-based simulation method has been used. The evaluation results show that large scale-free networks can be modeled and the propagation of Malware can be studied using the proposed approach. In addition, the effect of random and targeted immunization of nodes on the proposed models is evaluated as a case study.

In recent years, the Internet has become part of the requirements of human life. With the widespread use of the Internet, the Web, and online social networks, the number of vulnerabilities and security threats has increased significantly. Various types of Malwares (worms and viruses) have become a major threat to the security of systems and networks. In this regard, researchers are looking for ways to identify Malware and fight against them. One of the methods used in this field is to model the Malware propagation in order to identify and combat Malware by modeling its behavior. In this article, a Malware propagation model based on the propagation of epidemic diseases in a heterogeneous network structure, considering the devices connected to the network and the Internet, is introduced. modeling is done based on the Susceptible-Exposed-Infected-Recovered epidemic model for devices and Internet networks. The results show that the speed of Malware propagation in the proposed HD-SEIRS model is significantly reduced compared to the SEIR model. Also, in this article, the basic reproduction ratio (R_0 )  is calculated for the proposed model and the effect of parameter changes on the proposed model is investigated.

Today, the presence of methods and tools for large-scale modeling of different types of epidemic phenomena is a serious and critical requirement. Understanding these phenomena and discovering strategic solutions in various situations is also very important. Regarding the large number of agents and their complicated behaviors and lack of theoretical and analytical solutions, the need for simulation systems is so clear. In this paper, we introduce a software system for simulation of epidemic phenomena, especially Malware propagation in computer networks. This software system is able to simulate a large number of agents with different propagation models and parameters and show the graphical and statistical results dynamically. Distributed architecture, using real-world data, ability to use different kinds of epidemic models and dynamic visualization of simulation results, are some of the innovations of the proposed method. By performing different simulations, the relationships between infection density and simulation parameters such as the propagation model, the infection probability and the probability of vulnerability, were investigated over time. Additionally, the correctness of the simulation results is confirmed by comparing them to the results obtained from analytical methods.

modeling tools describe the real world complex problems well and might help analysts to explore constructive solutions for resolving the problems. In this paper, competition between Malware authors and security analysts is modeled and analyzed, using Graph Model for Conflict Resolution which is a comprehensive methodology in a non-quantitative non-cooperative perspective of game theory. This methodology has two main steps: modeling and Analysis. After removing infeasible combinations, 15 states which are possible to occur in reality, are studied in the modeling phase. Then, the ordinal preferences of the players over the states are represented. Various solution concepts are employed in this research for stability definition. Stability analysis shows that two states are predicted to be equilibria. The predicted outcomes indicate that Malware authors employ environment diagnostics and security analysts use system event monitoring along with global system state anomaly detection. Recent evidences are in conformity with the finding of this research.

Channel is one of the most important parts of a communication system as the medium of the propagation of electromagnetic waves. Being aware of how the channel affects the propagation waves is essential for the design, optimization, and performance analysis of a communication system. Along with conventional modeling schemes, in this paper, we present a novel propagation channel model. The proposed modeling strategy considers the 2-dimensional time-frequency response of the channel as an image. It models the distribution of these channel images using Deep Convolutional Generative Adversarial Networks (DCGANs). In addition, for the measurements with different user speeds, the user speed is considered as an auxiliary parameter for the model. StarGAN is used as an image-to-image translation technique to change the generated channel images with respect to the desired user speed. The performance of the proposed model is evaluated using a few existing evaluation metrics. Furthermore, as modeling the 2D time- frequency response is more general than the modeling of the channel only in time, the conventional metrics for evaluation of the channel models are not sufficient; therefore, a new metric is introduced in this paper. This metric is based on the Cepstral Distance Measure (CDM) between the mean autocorrelation of the generated samples and measurement data. Using this metric, the generated channels show significant statistical similarity to the measurement data.

In the design of marine pipelines, like other thin-walled structures, structural stability plays major role. Generally, two kinds of instabilities, namely global buckling and local buckling (collapse) may occur in marine pipelines. However, for deep water pipelines in addition to occurrence of collapse, another concern is the potential occurrence of propagating of this collapse along the pipe due to high external pressure.In the present study, details of 2-D and 3-D finite element modeling for collapse propagation simulation are outlined. In order to verify the accuracy and validity of the finite element modeling, the numerical results, obtained from nonlinear finite element analyses for severalpipe samples have been compared with the experimental results. These proposed 2-D and 3-D modeling methods are easily applicable. Also, the comparison shows that the results of these methods have very close agreement with the experimental behavior. Using nominal geometric properties, finding minimum required imperfections to eliminate bifurcation points and using corrected Ramberg-Osgood material behavior for steel pipe are the main characteristics of the present 3-D method. The study shows that this method gives more appropriate results than the previous proposed method by Toscano et al. (2002).

The fault rupture propagation phenomenon, spreading from the base rock through different layers of soil, is a matter of concern in many natural and man-made soil structures. The focus of this paper is to investigate reverse fault rupture propagation through two layers of sand deposits by means of numerical modeling. For this purpose, analyses are carried out for different permutations of the three typical materials: dense sand, medium dense sand and loose sand, considering five fault dip angles, 30, 45, 60, 75 and 90 degrees. The validity of numerical model was verified by simulating an experimental model of homogeneous soil layer subjected to reverse faulting. Further to the general trends found in fault rupture propagation in a single layer of soil, special attentions are devoted to the refraction of fault path in the interface of two materials as well as its concavity in the continuation. Moreover, four patterns of fault rapture propagation in two-layered sands, depending on their arrangements and fault dip angles, were concluded from the results.