The primary problem in the prevention and investigation of child sexual abuse (CSA) cases is the urgent need to prevent them and to investigate and prosecute offenders to protect vulnerable children swiftly and effectively. Child sexual abuse is still a grave and pervasive issue, often shrouded in secrecy, making it difficult for LEAs to identify other potential victims of identified perpetrators.

  • Investigation efforts for prosecution of CSA can consume over 80% of LEAs workforce.
  • The main challenge is to efficiently process large amounts of data and correlating information.

It is imperative to explore advanced technological solutions that use big data analytics and AI to enhance the investigative process while ensuring compliance with legal regulations.

PRESERVE will incorporate AI-based technologies, including comprehensive data analysis, User and Entity Behaviour Analytics (UEBA), and graph neural networks, to map and interpret complex connections between identified perpetrators and potential victims.

Moreover, computer vision techniques will be employed to detect sexual language and implications in images and videos. This will include analysing images to determine background locations and match identities with public images.

Additionally, false positives will be filtered out to expedite LEAs’ investigations.

Advanced AI-driven technologies employed include User and Entity Behaviour Analytics (UEBA), Computer Vision, and Graph Models.