Winning the War on Terror: Using “Top-K” Algorithm and CNN to Assess the Risk of Terrorists

Yaojie Wang, Xiaolong Cui and Peiyong He
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Yaojie Wang: Engineering University of PAP, China
Xiaolong Cui: Engineering University of PAP, China
Peiyong He: Engineering University of PAP, China

International Journal of Information Technology and Web Engineering (IJITWE), 2022, vol. 17, issue 1, 1-15

Abstract: From the perspective of counter-terrorism strategies, terrorist risk assessment has become an important approach for counter-terrorism early warning research. Combining with the characteristics of known terrorists, a quantitative analysis method of active risk assessment method with terrorists as the research object is proposed. This assessment method introduces deep learning algorithms into social computing problems on the basis of information coding technology. We design a special "Top-k" algorithm to screen the terrorism related features, and optimize the evaluation model through convolution neural network, so as to determine the risk level of terrorist suspects. This study provides important research ideas for counter-terrorism assessment, and verifies the feasibility and accuracy of the proposed scheme through a number of experiments, which greatly improves the efficiency of counter-terrorism early warning.

Date: 2022
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