CSAM

Research

We primarily work in developing new approaches to the prevention and detection of CSAM. We work with a range of international partners to achieve this, including:

• University of Tasmania

• Katalyst by Kindred Tech

• Lucy Faithfull Foundation

• ECPAT International

• ICMEC Australia

• UCL Jill Dando Institute of Security and Crime Science

Our work has been funded by the Australian Research Council and the Internet Watch Foundation.

Reports

• Online messages to reduce users’ engagement with child sexual abuse material: a review of relevant literature for the reThink chatbot

• An Analysis of Piracy Website Advertising in Brazil and Its Linkages to Child Exploitation Material

• How to implement online warnings to prevent the use of child sexual abuse material

• Warning messages to prevent illegal sharing of sexual images: Results of a randomised controlled experiment

Research Papers

• Scanlan, J., Watters, P. A., Prichard, J., Hunn, C., Spiranovic, C., & Wortley, R. (2022). Creating honeypots to prevent online child exploitation. Future Internet, 14(4), 121.

• Prichard, J., Wortley, R., Watters, P. A., Spiranovic, C., Hunn, C., & Krone, T. (2022). Effects of automated messages on internet users attempting to access “barely legal” pornography. Sexual Abuse, 34(1), 106-124.

• Krone, T., Spiranovic, C., Prichard, J., Watters, P., Wortley, R., Gelb, K., & Hunn, C. (2020). Child sexual abuse material in child-centred institutions: situational crime prevention approaches. Journal of sexual aggression, 26(1), 91-110.

• Islam, M., Mahmood, A. N., Watters, P., & Alazab, M. (2019). Forensic detection of child exploitation material using deep learning. Deep learning applications for cyber security, 211-219.

• Islam, M., Watters, P., Mahmood, A. N., & Alazab, M. (2019). Toward detection of child exploitation material: A forensic approach. Deep learning applications for cyber security, 221-246.

• Prichard, J., Krone, T., Spiranovic, C., & Watters, P. (2018). Transdisciplinary research in virtual space: can online warning messages reduce engagement with child exploitation material?. In Routledge handbook of crime science (pp. 309-319). Routledge.

• Watters, P. A. (2018). Modelling the Efficacy of Auto-Internet Warnings to Reduce Demand for Child Exploitation Materials. In Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2018 Workshops, BDASC, BDM, ML4Cyber, PAISI, DaMEMO, Melbourne, VIC, Australia, June 3, 2018, Revised Selected Papers 22 (pp. 318-329). Springer International Publishing.

• Prichard, J., Spiranovic, C., Gelb, K., Watters, P. A., & Krone, T. (2016). Tertiary education students' attitudes to the harmfulness of viewing and distributing child pornography. Psychiatry, Psychology and Law, 23(2), 224-239.

• Prichard, J., Watters, P., Krone, T., Spiranovic, C., & Cockburn, H. (2015). Social media sentiment analysis: A new empirical tool for assessing public opinion on crime?. Current Issues in Criminal Justice, 27(2), 217-236.

• Prichard, J., Spiranovic, C., Watters, P., & Lueg, C. (2013). Young people, child pornography, and subcultural norms on the Internet. Journal of the American Society for Information Science and Technology, 64(5), 992-1000.

• Watters, P. A., Lueg, C., Spiranovic, C., & Prichard, J. (2013). Patterns of ownership of child model sites: Profiling the profiteers and consumers of child exploitation material. First Monday.

• Islam, M., Watters, P., Yearwood, J., Hussain, M., & Swarna, L. A. (2013). Illicit image detection: an MRF model based stochastic approach. In Innovations and Advances in Computer, Information, Systems Sciences, and Engineering (pp. 467-479). Springer New York.

• Islam, M., Watters, P., Yearwood, J., Hussain, M., & Swarna, L. A. (2013). Illicit image detection using erotic pose estimation based on kinematic constraints. In Innovations and Advances in Computer, Information, Systems Sciences, and Engineering (pp. 481-495). Springer New York.

• Prichard, J., Watters, P. A., & Spiranovic, C. (2011). Internet subcultures and pathways to the use of child pornography. Computer Law & Security Review, 27(6), 585-600.

• Islam, M., Watters, P., & Yearwood, J. (2011, November). Child face detection using age specific luminance invariant geometric descriptor. In 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) (pp. 34-39). IEEE.

• Islam, M., Watters, P. A., & Yearwood, J. (2011). Real-time detection of children’s skin on social networking sites using Markov random field modelling. Information Security Technical Report, 16(2), 51-58.