Using Traces from IoT Devices to Solve Criminal Cases

During a criminal investigation, the evidence collection process produces an enormous amount of data. These data are present in many medias and IoT devices that are extracted as crime evidences (USB flash drives, smartphones, hard drives, computers, drones, smartwatches, AI speakers, sensors etc). Due to this data volume, the manual analysis is slow and costly. This work fulfills this gap by presenting a data extraction and processing platform for crime evidence analysis. Our proposed platform leverages a lambda architecture and uses a set of tools and frameworks such as Hadoop HDFS, Kafka, Spark and Docker to analyze a big volume of data at an acceptable time. We also present an example of the proposed platform in use by the State Attorney Office of Rio Grande do Norte (Brazil), where some evaluative tests have been carried out.