Researchers can predict terrorist behaviors with more than 90 percent accuracy
“Researchers at Binghamton have proposed a comprehensive new framework, the Networked Pattern Recognition (NEPAR) Framework, by defining the useful patterns of attacks to understand behaviors, to analyze patterns and connections in terrorist activity, to predict terrorists’ future moves, and finally, to prevent and detect potential terrorist behaviors.
Using data on more than 150,000 terrorist attacks between 1970 and 2015, Binghamton University PhD student Salih Tutun developed a framework that calculates the relationships among terrorist attacks (e.g. attack time, weapon type) and detects terrorist behaviors with these connections. Mohammad Khasawneh, professor and head of the Systems Science and Industrial Engineering (SSIE) department at Binghamton University, assisted and advised Tutun with his research. In the framework, there are two main phases: (1) building networks by finding connections between events, and (2) using a unified detection approach that combines proposed network topology and pattern recognition approaches. Firstly, the framework identifies the characteristics of future terrorist attacks by analyzing the relationship between past attacks. Comparing the results with existing data shows that the proposed method was able to successfully predict most of the characteristics of attacks with more than 90% accuracy.”