6533b86cfe1ef96bd12c80dd

RESEARCH PRODUCT

Graph Comparison and Artificial Models for Simulating Real Criminal Networks

Lucia CavallaroAntonio LiottaGiacomo FiumaraFrancesco CurreriAnnamaria FicaraPasquale De MeoOvidiu Bagdasar

subject

Settore INF/01 - Informaticabusiness.industryComplex networksContext (language use)Network scienceGraph theoryComplex networkGraph comparisonMachine learningcomputer.software_genreNetwork topologyCriminal networksGraph similarityGraph theorySocial network analysisGraph (abstract data type)Graph matchingArtificial intelligencebusinessResilience (network)Social network analysiscomputer

description

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.

yearjournalcountryeditionlanguage
2021-01-01
https://doi.org/10.1007/978-3-030-65351-4_23