Investigation of information security issues for graph databases suitable for big data processing while detecting money laundering and terrorism financing cases

Abstract

The information security (IS) issues in the currently popular graph database management systems (DBMS), suitable for big data processing and storing information created during the generation of criminal cases on money laundering and financing of terrorism (ML/FT), are examined. This paper continues the previous authors’ research and aims to analyze IS threats and vulnerabilities of graph DBMS. These DBMS differ from the relational ones in the type of stored data and the principle of their storage; therefore the compiling of a list of IS threats is urgent due to its absence on a global scale. The original IS threat list and methods for protecting against them, as well as some recommendations for eliminating vulnerabilities used by IS threats are proposed. The obtained results are based on the analysis of IS threats for conventional DBMS and taking into account the peculiarities of graph DBMS, their structure as well as vulnerabilities of specific graph DBMS.

Keywords

• money laundering, terrorism financing, ml/ft, information security, typology, big data, database management system (dbms), information security threats, vulnerabilities.