Hypotheses Analysis and Assessment in counter-terrorism activities: a method based on OWA and Fuzzy Probabilistic Rough Sets

This article presents a new interactive method to analyze and assess hypotheses, and its application to terrorism events. The method combines probability, fuzzy, and rough set theories and supports decision makers and analysts of counterterrorism in the analysis of intelligence information by using behavioral models of known terrorist groups. Starting from intelligence information about possible attack patterns, the proposed method uses two parameters allowing derivation and analysis of a wide range of hypotheses, and their assessment on the basis of different support levels of evidence. The evaluation of results has been done on real data relating to five years (2012–2016) of terrorist activities extracted from the Global Terrorism Database.