Data Integrity Based Attacks in Investigative Domains: How Companies Are Exploiting Data Science to Thwart Investigative Outcomes

The Trustworthy Data Engineering Laboratory (TRUST Lab) has been working with the World Bank, the Federal Bureau of Investigation (FBI), the Environmental Protection Agency (EPA), and the City of Cincinnati to help solve a common problem faced by many organizations involved in data driven investigations: companies and entities that attempt to disguise malicious activities through attacks on the integrity of available data.

In this talk we will explore the challenge of assuring data integrity in heterogenous data systems that face the challenges of velocity, variety, and volume that accompany the domain of Big Data. We will examine real case studies in debarrment and corruption in international procurement with the World Bank, investigations into violations of the Foreign Corrupt Practices Act with the FBI, cases of violations of the Resource Conservation and Recovery Act with the EPA, and human rights abuses of low income citizens by corporate slum-lords in the city of Cincinnati. In each of these cases we will show how malicious actors manipulated the data collection and data analytics process either through misinformation, abuse of regional corporate legal structures, collusion with state actors, or knowledge of underlying predictive analytics algorithms to damage the integrity of data used by machine learning and predictive analytic processes, or the outcomes derived from these processes, to avoid regulatory oversite, sanctions, and investigations launched by national and multi-national authorities.