The Panama Papers represent a large set of relationships between people, companies, and organizations that had affairs with the Panamanian offshore law firm Mossack Fonseca, often due to money laundering. In their work, the Boise State researchers addressed the problem of identifying bad entities (people or companies) by leveraging the information contained in the Panama Papers network. They proposed a new algorithm that computes a suspiciousness score for each entity appearing in the Panama Papers according to its connections to other known bad entities. The ground truth for bad entities in the Panama Papers is retrieved from several international blacklists of sanctioned people. Experiments show that the proposed algorithm is highly accurate.
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Edoardo Serra, Francesca Spezzano and Mikel Joaristi
Professors Edoardo Serra, Francesca Spezzano and doctoral student Mikel Joaristi won the best paper award at the International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI 2018) in conjunction with the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018) for their work on “Inferring Bad Entities through the Panama Papers Network.” The conference, sponsored by the Association for Computing Machinery and the Institute for Electrical Electronics Engineers, was held in Barcelona, Spain, Aug. 28-31.