Rapid Identification of Indecent Images of Children (IIOC) and Victim Identification in Digital Investigations

Research Team and stakeholders – Secure Societies Institute (University of Huddersfield).

Dr Simon Parkinson is leading the project ‘Rapid Identification of Indecent Images of Children and Victim Identification in Digital Investigations’.

Other members of SSI involved in the project are; Dr Nadia Wager (HHS), Professor Rachel Armitage (HHS), Professor Jason Roach (HHS); Staff from the Centre for Cyber Security; Dr Saad Khan (SCE) and Dr Abdul Jabbar (HBS) are also part of the research team. This project is supported by the University of Huddersfield and Kursch Consult Ltd.

A Research Fellow is being appointed to work on the project.

Other organisations who will be supporting the project include; West Yorkshire, Derbyshire and West Midlands police forces; technology companies providing current technology solutions (Kursch); the third sector Nation Working Group for Sexually Exploited Children; and Young People and National Crime Agency.

Timescale

The project commenced in January 2022 and will be completed by January 2024.

Research context

In the UK and globally, police forces and law enforcement agencies (LEAs) are facing huge demand to view, process and analyse digital evidence. The continuous increase of computer, mobile and internet device use has created a massive growth in digital policing requirements. Arrests for Indecent Images of Children (IIOC) have risen by a factor of 25 over the previous decade, resulting in the demand to investigate 850 per month in 2020/21. Yet investigative processes and resources have largely not changed. The pervasive use of computer-based technology means every individual has a digital footprint which, whether as offender or victim, is pertinent to almost all investigations. Investigators can be presented with massive amounts of data per case (can be over 60 terra bites).

Project Objectives

This project will develop knowledge and resources to reduce time taken by police investigators to identify victims. It will also support investigator welfare.

Some of the key objectives of the project are:

  • To work with external stakeholders to create a replica technology stack at Huddersfield focussing on those related to time taken to identify IIOC images, victim identification, and investigator welfare.
  • Applying automated planning and scheduling techniques to develop and measure impact from a new software architecture capable of not only reducing overall processing time but enabling an earlier identification of images.
  • Improved use of IIOC images from multiple police forces to develop more capable automatic classification techniques, overcoming sharing challenges through utilising federated learning.
  • Embedding victim identification techniques early in the process through using police archive data, as well as other data sources to perform open-source intelligence techniques.

This project demonstrates SSI’s emphasis on interdisciplinary collaboration and our objectives of supporting real world research which will have positive societal impacts.

https://research.hud.ac.uk/institutes-centres/ssi/projects/

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