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Algorithms and methods for organised cybercrime analysis [Recurso eletrónico] / Jan William Johnsen

Autor: JOHNSEN, Jan WilliamIdioma: Inglês.Publicação: Gjovik : [s.n.], 2016Descrição física: 1 CD-ROM; 12 cmAssunto: 225700 | 322772 | 347107 | 321724 | 321297 | 334284 | 334326Resumo: Contents. Preface. Acknowledgment. Abstract. Abbreviations. Glossary. Contents. List of Figures. List of Tables. Listings. 1 Introduction. 1.1 Topics covered by the project. 1.2 Keywords. 1.3 Problem description. 1.4 Justification, motivation and benefits. 1.5 Research questions. 1.6 Contributions. 1.7 Thesis outline. 2 Background. 2.1 Organised crime. 2.1.1 Organised crime groups typology. 2.1.2 Organised crime analysis. 2.2 Machine learning. 2.2.1 Machine learning methods. 2.2.2 Features and feature quality. 2.2.3 Data preprocessing methods. 2.2.4 Applications and challenges. 2.3 Graph theory. 2.3.1 Vertex degree. 2.3.2 Subgraph. 2.3.3 Graph representation. 2.4 Social network analysis. 2.4.1 Levels of analysis. 2.4.2 Graph construction approaches. 2.4.3 Applications and challenges. 2.5 Summary. 3 Previous work. 4 Choice of methods. 4.1 Dataset. 4.1.1 Randomly generated datasets. 4.1.2 Enron-email corpus dataset. 4.2 Pre-processing. 4.3 Experimental design. 4.3.1 Features for identification of individuals and groups. 4.3.2 Graph-based construction techniques for digital forensics. 5 Experiments. 5.1 Experimental design and environment setup. 5.1.1 Dataset. 5.1.2 Dataset validation. 5.2 Experiment execution. 5.2.1 Features for identification of individuals and groups. 5.2.2 Graph-based construction techniques for digital forensics. 5.3 Experiment results. 5.3.1 Results of Social Network Analysis. 5.3.2 Results of graph-based construction techniques. 5.4 Experiment discussion. 5.4.1 Features for identification of individuals and groups. 5.4.2 Graph-based construction techniques for digital forensics. 6 Discussion, conclusion and further work. 6.1 Theoretical implications. 6.2 Practical recommendations. 6.3 General discussion. 6.4 Conclusion. 6.5 Further work. Bibliography. A Enron employee list. B Complete graphs. C Social network analysis results. D Graph construction results. E SQL table export. F Enron social network analysis. G Graph construction.
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Monografias Biblioteca da Polícia Judiciária
PJCD279 (Browse shelf) PJCD279 Available PJ1CD279

Tese de mestrado em "Information Security" apresentada à "Norwegian University of Science and Technology", tendo como orientadores Katrin Franke, Slobodan Petrovic. Ficheiro de 2,16 MB em formato PDF (146 p.).

Contents. Preface. Acknowledgment. Abstract. Abbreviations. Glossary. Contents. List of Figures. List of Tables. Listings. 1 Introduction. 1.1 Topics covered by the project. 1.2 Keywords. 1.3 Problem description. 1.4 Justification, motivation and benefits. 1.5 Research questions. 1.6 Contributions. 1.7 Thesis outline. 2 Background. 2.1 Organised crime. 2.1.1 Organised crime groups typology. 2.1.2 Organised crime analysis. 2.2 Machine learning. 2.2.1 Machine learning methods. 2.2.2 Features and feature quality. 2.2.3 Data preprocessing methods. 2.2.4 Applications and challenges. 2.3 Graph theory. 2.3.1 Vertex degree. 2.3.2 Subgraph. 2.3.3 Graph representation. 2.4 Social network analysis. 2.4.1 Levels of analysis. 2.4.2 Graph construction approaches. 2.4.3 Applications and challenges. 2.5 Summary. 3 Previous work. 4 Choice of methods. 4.1 Dataset. 4.1.1 Randomly generated datasets. 4.1.2 Enron-email corpus dataset. 4.2 Pre-processing. 4.3 Experimental design. 4.3.1 Features for identification of individuals and groups. 4.3.2 Graph-based construction techniques for digital forensics. 5 Experiments. 5.1 Experimental design and environment setup. 5.1.1 Dataset. 5.1.2 Dataset validation. 5.2 Experiment execution. 5.2.1 Features for identification of individuals and groups. 5.2.2 Graph-based construction techniques for digital forensics. 5.3 Experiment results. 5.3.1 Results of Social Network Analysis. 5.3.2 Results of graph-based construction techniques. 5.4 Experiment discussion. 5.4.1 Features for identification of individuals and groups. 5.4.2 Graph-based construction techniques for digital forensics. 6 Discussion, conclusion and further work. 6.1 Theoretical implications. 6.2 Practical recommendations. 6.3 General discussion. 6.4 Conclusion. 6.5 Further work. Bibliography. A Enron employee list. B Complete graphs. C Social network analysis results. D Graph construction results. E SQL table export. F Enron social network analysis. G Graph construction.

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