Arquitetura de microsserviços para processamento de imagens relevantes em evidências de crimes digitais

Abstract

Digital forensics is a branch of computer science that uses computational techniques to analyze criminal evidence with greater speed and accuracy. In the context of the Brazilian justice system, during a criminal investigation, forensic specialists extract, decode, and analyze the evidence collected to allow the prosecutor to make legal demands for a prosecution. These experts have a very short time to analyze to find criminal evidence can take a long time. To solve this problem, this paper proposes ARTEMIS (A micRoservice archiTecturE for imagesin criMe evIdenceS or Microservice Architecture for images in criminal evidence) an architecture for classifying large amounts of image files present in evidence using open-source software. The image classification module contains some pre-trained classifiers, considering the need of forenses analysts from the MPRN (Rio Grande do Norte Public Ministry). Models were built to identify specific types of objects with for example: firearms, ammunition, Brazilian ID cards, text documents, cell phone screen captures enudez. The results obtained show that the system obtained good precision in most cases. This is extremely important in the context of this research, where false positives should be avoided in order to save analysts’ work time. In addition, the proposed architecture was able to accelerate the process of evidence analysis.