Experts at Lancaster University are part of a $10 million research programme aiming to halt online child sexual abuse launched by End Violence Against Children (EVAC).
The team are helping to develop new technology to help law enforcement investigate child sexual abuse on the internet. The project will use artificial intelligence to identify images, helping police to catch perpetrators and protect children.
Globally renowned for her research into online child abuse, Professor Corinne May-Chahal, a Co-director of Security Lancaster, is working with Professor Awais Rashid and Dr Claudia Peersman at the University of Bristol to enhance iCOP, the research team's artificial intelligence software.
iCOP was created by the team to flag new or previously unknown child sexual abuse material, and iCOP 2.0 will extend the software's reach to Southeast Asia.
The team has just received funding from the End Violence Against Children Fund to extend this work into South East Asia.
"The rates of online child sexual abuse material in Southeast Asia are growing, and technologies for law enforcement need to keep pace," said Professor Awais Rashid, Professor of Cyber security at the University of Bristol and Director of the newly established National Research Centre on Privacy, Harm Reduction and Adversarial Influence Online, REPHRAIN.
"Our new AI-based tool will provide law enforcement with sophisticated techniques to apprehend perpetrators and, ultimately, safeguarding victims."
Professor May-Chahal, one of the lead researchers on the new project, said: "Through my recent analysis of child sexual abuse media (CSAM) of Interpol and NGO databases we know that CSAM from the region is under-reported. I will be working with law enforcement officers across the region to encourage use of iCOP 2.0 and strengthen their response to online child sexual abuse victimisation".
In addition to close collaboration with law enforcement in ASEAN (Association of Southeast Asian Nations) countries, the project will involve wider outreach (advocacy and training) to law enforcement across the region through events and online tutorials.
The solution proposed in this project will allow investigators to automatically:
- Detect victims at acute risk and support interventions to prevent further victimisation
- Assign degrees of importance and urgency to items of evidence in order to assess online child sex offenders' potential danger to society
- Find useful evidence in a timely manner
