Money laundering presents a pervasive challenge, burdening society by financing illegal
activities. To more effectively combat and detect money laundering, the use of network …

The present study analyzes the offshoring network constructed from the information
contained in the Panama Papers, characterizing worldwide regions and countries as well as …

Botnets are an ever-growing threat to private users, small companies, and even large
corporations. They are known for spamming, mass downloads, and launching distributed …

Abstract The ICIJ Offshore Leaks Database represents a large set of relationships between
people, companies, and organizations involved in the creation of offshore companies in tax …

What are the criteria used by Financial Action Task Force (FATF) and the European Union to
blacklist jurisdictions at high-risk of money laundering? What are the countries at highest risk …

Interpretability is a key feature to broaden a conscious adoption of machine learning models
in domains involving safety, security, and fairness. To achieve the interpretability of complex …

In the BigData era, large graph datasets are becoming increasingly popular due to their
capability to integrate and interconnect large sources of data in many fields, eg, social …

Cash flow prediction of a bank is an important task as it is not only related to liquidity risk but
is also regulated by financial authorities. To improve the prediction, a graph analysis of bank …

Detecting Malware is an interesting research area, however, as the polymorphic nature of
the latter makes it difficult to identify, particularly when using Hash-based detection methods …

Starting in 2013, the International Consortium of Investigative Journalists released a series
of networks, known as the Offshore Leaks Networks, detailing the information of entities and …