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A Generative Model for the Layers of Terrorist Networks

Oludare Adeniji, David S. Cohick, Ralucca Gera, Victor G. Castro, Akrati Saxena
2017 Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 - ASONAM '17  
This creates the need for generative network models based on the existing data.  ...  We propose generative models to create synthetic dark layers of both types.  ...  This model can be enhanced through a better understating of the topology of terrorist networks from more data.  ... 
doi:10.1145/3110025.3110153 dblp:conf/asunam/AdenijiCGCS17 fatcat:m7bqb4cca5ge7lhp5uqfomqdzm

Prediction of Future Terrorist Activities Using Deep Neural Networks

M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud
2020 Complexity  
This concludes that DNN is a suitable model to be used for predicting the behavior of terrorist activities.  ...  Our experiments also demonstrate that the dataset for terrorist activities is big data; therefore, a DNN is a suitable model to process big data and understand the underlying patterns in the dataset.  ...  DF-461-156-1441. e authors, therefore, gratefully acknowledge the DSR for the technical and financial support.  ... 
doi:10.1155/2020/1373087 fatcat:ihq6vpk4vrgppm5ye2hmnfsvva

Data Mining Approach to Counterterrorism

Stanley Onyekachi Uche, University of Nigeria nsukka, Nigeria, Norbert Tsopze, Deborah Uzoamaka Ebem
2020 Advances in Multidisciplinary & Scientific Research Journal Publication  
To improve on the work, extra features were introduced in the dataset and a deep neural network (DNN) model for predicting the success of terrorist attacks was developed.  ...  This study reports on the use of available data about terrorist incidents all around the world in combating terrorism with the application of deep learning.  ...  In this work deep neural network model was used to predict the success of terrorist attacks.  ... 
doi:10.22624/aims/cisdi/v11n2p5 fatcat:2avd64ucvfgqfesh23oczpuynm

Generation of Realistic Social Network Datasets For Testing of Analysis and Simulation Tools

Maksim Tsvetovat, Kathleen M. Carley
2005 Social Science Research Network  
Testing large-scale dynamic network simulation packages such as NetWatch[34] requires a large quantity of test data to be available for each of the experiments.  ...  The test data includes initial topologies of agents' social networks and specification of knowledge networks for each of the agents to fit an empirically derived distribution of knowledge.  ...  function for each of the layers to generate edges at the given layer.  ... 
doi:10.2139/ssrn.2729296 fatcat:c7vgqks7frbxvp5p5v7ifjlape

Counterterrorism for Cyber-Physical Spaces: A Computer Vision Approach

Cascavilla Giuseppe, Johann Slabber, Fabio Palomba, Dario Di Nucci, Damian A. Tamburri, Willem-Jan Van Den Heuvel
2020 Zenodo  
This paper addresses the aforementioned issue with ALTer a framework featuring computer vision and Generative Adversarial Neural Networks (GANs) over terrorist scenarios.  ...  We obtained the data for the terrorist scenarios by creating a synthetic dataset, exploiting the Grand Theft Auto V (GTAV) videogame, and the Unreal Game Engine behind it, in combination with OpenStreetMap  ...  Training the Generative Adversarial Network. To model the simulation, we rely on StyleGAN architecture.  ... 
doi:10.5281/zenodo.4534149 fatcat:luhzeaydvfempc5foaqxhhsyay

Counterterrorism for Cyber-Physical Spaces: A Computer Vision Approach

Cascavilla Giuseppe, Johann Slabber, Fabio Palomba, Dario Di Nucci, Damian A. Tamburri, Willem-Jan Van Den Heuvel
2020 Zenodo  
This paper addresses the aforementioned issue with ALTer a framework featuring computer vision and Generative Adversarial Neural Networks (GANs) over terrorist scenarios.  ...  We obtained the data for the terrorist scenarios by creating a synthetic dataset, exploiting the Grand Theft Auto V (GTAV) videogame, and the Unreal Game Engine behind it, in combination with OpenStreetMap  ...  Training the Generative Adversarial Network. To model the simulation, we rely on StyleGAN architecture.  ... 
doi:10.5281/zenodo.4534150 fatcat:shq6icuabvf4xgegp2lm52lsqy

Models and architectures for emergency management

I. Giordani, F. Archetti
2016 Journal of Ambient Intelligence and Humanized Computing  
a virtual layer of measure in a wireless sensor network (WSN).  ...  Level 4 (Process refinement) (Pires et al. 2016 ) is a meta-layer, whose major role is to generate, train and tune the fusion models, which are exploited by lower layers of the system and, in particular  ... 
doi:10.1007/s12652-016-0417-9 fatcat:gu4fxtgovzcjpdam5guduz2w7y

Information integration via hierarchical and hybrid bayesian networks

Haiying Tu, J. Allanach, S. Singh, K.R. Pattipati, P. Willett
2006 IEEE transactions on systems, man and cybernetics. Part A. Systems and humans  
The general Bayesian networks are adopted in the top (decision) layer to address global assessment for a specific question (e.g., "Is target A under terrorist threat?"  ...  Hierarchical is in terms of the model structure and hybrid stems from our usage of both general Bayesian networks (BNs) and hidden Markov models (HMMs, a special form of dynamic BNs).  ...  The general Bayesian networks are adopted in the top (decision) layer to address global assessment for a specific question (e.g., "Is target A under terrorist threat?"  ... 
doi:10.1109/tsmca.2005.859180 fatcat:ngobr2gt5fawxdof5a3zqhulxe

Winning the War on Terror

Yaojie Wang, Xiaolong Cui, Peiyong He
2022 International Journal of Information Technology and Web Engineering  
We design a special "Top-k" algorithm to screen the terrorism related features, and optimize the evaluation model through convolution neural network, so as to determine the risk level of terrorist suspects  ...  Combining with the characteristics of known terrorists, a quantitative analysis method of active risk assessment method with terrorists as the research object is proposed.  ...  Through the social network analysis software SNA and ORA, Xiaopeng (2018) proposed a terrorist network model, revealing the characteristics of terrorist networks.  ... 
doi:10.4018/ijitwe.288038 fatcat:pupklzenlndcbhyu2juaekzcpy

Terrorist Group Behavior Prediction by Wavelet Transform-Based Pattern Recognition

Ze Li, Duoyong Sun, Bo Li, Zhanfeng Li, Aobo Li
2018 Discrete Dynamics in Nature and Society  
Our ideas rely on social network analysis to model the terrorist group and extract relevant features for group behaviors.  ...  There are certain dynamic characteristics of terrorist groups, such as periodic features and correlations between the behavior and the network.  ...  Acknowledgments This research is supported by the National Natural Science Foundation of China, nos. 71473263 and 71704184. Discrete Dynamics in Nature and Society  ... 
doi:10.1155/2018/5676712 fatcat:b7kslw7q5bhctkpp5viehjjk3a

Terrorism Prediction Using Artificial Neural Network

Ghada M.A. Soliman, Tarek H.M. Abou-El-Enien
2019 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
The findings of this research may serve as an alarm tool to determine the terrorist groups' networks and so minimize the terrorist attacks.  ...  The main purpose of this research is to develop a hybrid computational intelligent algorithm (framework) as a decision support (DS) tool for terrorism phenomenon that has been defeated for years by governments  ...  When the Activation functions are "Radbas' for the hidden layer, 'tansig' for the output layer as well as the number of Neurons=25, the network produced the following output: Prediction Accuracy: 75 %  ... 
doi:10.18280/ria.330201 fatcat:ht7c2riczraqbpvcsysokcpqtq

Null Model and Community Structure in Multiplex Networks

Xuemeng Zhai, Wanlei Zhou, Gaolei Fei, Weiyi Liu, Zhoujun Xu, Chengbo Jiao, Cai Lu, Guangmin Hu
2018 Scientific Reports  
In this paper, we propose a new general measure of nodes to fill this gap and generate a novel Null Model with Redundancy (NMR) for multiplex networks.  ...  It is not possible to build the null model of single network for each layer of network separately because each layer is interrelated.  ...  In a more general sense, the NMR is a general null model for any multiple-relationship system such as the social networks utilized above.  ... 
doi:10.1038/s41598-018-21286-0 pmid:29459696 pmcid:PMC5818485 fatcat:gh6nrgyz5felti7pvy4tjlctvi

Networked Data Mining Based on Social Network Visualizations

Yu-Bin YANG, Ni LI, Yao ZHANG
2008 Journal of Software (Chinese)  
The data model is based on a network of associations -each field in a dataset represents a layer in the model and each possible value for an ordinal field is a node in that layer.  ...  In the domain of link prediction, a probability model is often generated that attempts to reflect the linkages within the network.  ... 
doi:10.3724/sp.j.1001.2008.01980 fatcat:fqsvbpp6irgrphwmc47xgruefu

An Agent-based Simulation of Extremist Network Formation through Radical Behavior Diffusion

Carlos Sureda, Benoit Gaudou, Frederic Amblard
2017 Proceedings of the 9th International Conference on Agents and Artificial Intelligence  
This paper also provides a non-exhaustive but detailed survey of the state of the art on the agent-based terrorist networks modelling.  ...  In this paper, an agent-based approach is used to simulate the process of radicalization and creation of a terrorist network, and the link between both processes.  ...  Likewise, the allegiance vector is built from qualitative data. (North, et al., 2004) generates a TN from a sample of a given network.  ... 
doi:10.5220/0006198602360243 dblp:conf/icaart/GutierrezGA17 fatcat:mqqkgres7jhq5krqrhrirnvjhq

Intuitive visualization of the intelligence for the run-down of terrorist wire-pullers [article]

Yoshiharu Maeno, Yukio Ohsawa
2008 arXiv   pre-print
The investigation of the terrorist attack is a time-critical task.  ...  This paper presents a computational method to analyze the intelligence data set on the collective actions of the perpetrators of the attack, and to visualize it into the form of a social network diagram  ...  Missing links in a hierarchical network is predicted by estimating the parameters of a dendrogram, which generates the observed network structure [4] .  ... 
arXiv:0805.3972v2 fatcat:bty6veygx5dvzkjdok5iy2szba
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