Art Crime Does not pay: Multiplexed Social Network Analysis in Cultural Heritage Trafficking Forensics

Abstract

Nowadays, crimes connected to cultural heritage can feature as a staple for organised crime networks and act as financial enablers for international conflicts, including terrorism organisations and even inter-state conflicts, in several ways. Goods of cultural significance include a range of valuable objects related to human cultures, like works of art, historical artefacts, and other antiques, but also forgeries based on such objects. These crimes are almost always transnational, for instance, involving theft or looting in one country and goods moved across borders to be sold. This article presents an intelligence methodology based on Social Network Analysis (SNA) techniques that can support law enforcement agencies (LEAs) in their daily struggle against criminals that also pose a threat to national security. The methodology proposed is based on the building of a blended, multiplexed social network graph, deriving from the fusion of a diverse set of data sources, both in the open-source domain (OSINT) and in the classified domain. We will present data collection methods, correlation between sources, possible ways to generate blended links between individuals that retain information from different sources, and SNA techniques applied to intelligence and investigations. The article provides an answer to the following research questions: how we can detect and identify criminal activities and networks related to cultural goods crimes, how we can assist LEAs in countering illicit trafficking, and how we can ensure that art crime does not pay.