Fraud Prevention Within the Brazilian Governmental Public-Key Infrastructure

Digital certificates are massively used in government systems in Brazil. However, in the last few years, cases of fraud were started to be continuously reported. Current Brazil’s issuing process is slow, costly and susceptible to failure. Thus, this present work proposes an automatic fraud detection process using machine learning in a hybrid approach. The method aims to categorize the applicant’s application at the level of dangerousness, that is, the chances of being a fraud. The proposed method was tested with data from real dossiers, whereas the fraudsters’ data were synthetically created. The results were satisfactory, showing that it is possible to reduce the execution time, reduce costs, and increase the process’s safety.

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