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