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International Conference on Complex Networks and Their Applications

COMPLEX NETWORKS 2020 2020: Complex Networks & Their Applications IX pp 286–297Cite as

Graph Comparison and Artificial Models for Simulating Real Criminal Networks

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 944))

Abstract

Network Science is an active research field, with numerous applications in areas like computer science, economics, or sociology. Criminal networks, in particular, possess specific topologies which allow them to exhibit strong resilience to disruption. Starting from a dataset related to meetings between members of a Mafia organization which operated in Sicily during 2000s, we here aim to create artificial models with similar properties. To this end, we use specific tools of Social Network Analysis, including network models (Barabási-Albert identified to be the most promising) and metrics which allow us to quantify the similarity between two networks. To the best of our knowledge, the DeltaCon and spectral distances have never been applied in this context. The construction of artificial, but realistic models can be a very useful tool for Law Enforcement Agencies, who could reconstruct and simulate the evolution and structure of criminal networks based on the information available.

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Author information

Authors and Affiliations

  1. School of Computing and Engineering, University of Derby, Kedleston Road, Derby, DE22 1GB, UK

    Lucia Cavallaro & Ovidiu Bagdasar

  2. DMI Department, University of Palermo, via Archirafi 34, 90123, Palermo, Italy

    Annamaria Ficara & Francesco Curreri

  3. MIFT Department, University of Messina, Viale Ferdinando Stagno d’Alcontres 31, 98166, Messina, Italy

    Giacomo Fiumara

  4. DICAM Department, University of Messina, Viale Giovanni Palatuci 13, 98168, Messina, Italy

    Pasquale De Meo

  5. Faculty of Computer Science, Free University of Bozen-Bolzano, Piazza Domenicani 3, 39100, Bolzano, Italy

    Antonio Liotta

Authors
  1. Lucia Cavallaro
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  2. Annamaria Ficara
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  3. Francesco Curreri
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  4. Giacomo Fiumara
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  5. Pasquale De Meo
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  6. Ovidiu Bagdasar
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  7. Antonio Liotta
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Corresponding author

Correspondence to Lucia Cavallaro .

Editor information

Editors and Affiliations

  1. Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Madrid, Madrid, Spain

    Rosa M. Benito

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LE2I, UFR Sciences et Techniques, Université de Bourgogne, Dijon, France

    Hocine Cherifi

  4. Grupo Interdisciplinar de Sistemas Complejos, Departamento de Matematicas, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Esteban Moro

  5. Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Luis Mateus Rocha

  6. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Marta Sales-Pardo

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Cavallaro, L. et al. (2021). Graph Comparison and Artificial Models for Simulating Real Criminal Networks. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_23

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  • DOI: https://doi.org/10.1007/978-3-030-65351-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65350-7

  • Online ISBN: 978-3-030-65351-4

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