Cyber strategies play a role in combating child sexual abuse material (CSAM). These strategies aim to detect offenders and prevent them from accessing and producing CSAM, or to identify victims. This paper explores five cyber strategies: peer-to-peer network monitoring, automated multi-modal CSAM detection tools, using web crawlers to identify CSAM sites, pop-up warning messages, and facial recognition. This research synthesis captures the background of each strategy, how it works and the evaluative research, along with the benefits, limitations and implementation considerations, offering a practical overview for a broad audience.
References
URLs correct as at May 2021
*included in review
Açar KV 2017. Web cam child prostitution: An exploration of current and futuristic methods of detection. International Journal of Cyber Criminology 11(1): 98–109. https://doi.org/10.5281/zenodo.495775
Akerman T 2019. Hi-tech damage control. The Australian, 22 May. https://www.theaustralian.com.au/inquirer/hitech-damage-control/news-st…
Australian Federal Police 2017. Annual report 2016–17. Canberra: Australian Federal Police. https://www.afp.gov.au/about-us/publications-and-reports/annual-reports
Australian Transaction Reports and Analysis Centre 2019. Combating the sexual exploitation of children for financial gain: Activity indicators. https://www.austrac.gov.au/business/how-comply-guidance-and-resources/g…
*Baines V 2018. Online child sexual exploitation: Towards an optimal international response. Journal of Cyber Policy 4(2): 197–215. https://doi.org/10.1080/23738871.2019.1635178
Balfe M, Gallagher B, Masson H, Balfe S, Brugha R & Hackett S 2015. Internet child sex offenders’ concerns about online security and their use of identity protection technologies: A review. Child Abuse Review 24(6): 427–439. https://doi.org/10.1002/car.2308
Broadhurst R 2019. Child sex abuse images and exploitation materials. In R Leukfeldt & T Holt (eds), The human factor of cybercrime. Routledge: 310–36
Bursztein E, Clarke E, DeLaune M, Eliff DM, Hsu N, Olson L, Shehan J, Thakur M, Thomas K & Bright T 2019. Rethinking the detection of child sexual abuse imagery on the internet. Paper presented at the World Wide Web Conference, San Francisco, CA: 2601–2607
*Canadian Centre for Child Protection 2017. Groundbreaking tool to remove online child sexual abuse material. https://protectchildren.ca/en/press-and-media/news-releases/2017/projec…
Christensen LS, Rayment-McHugh S, Prenzler T, Chiu YN & Webster J 2021. The theory and evidence behind law enforcement strategies that combat child sexual abuse material. International Journal of Police Science and Management. Advance online publication. https://doi.org/10.1177/14613557211026935
Clarke RV 1980. Situational crime prevention: Theory and practice. British Journal of Criminology 20(2): 136–47
Clarke RV 1997. Situational crime prevention: Successful case studies. Albany, NY: Harrow and Heston
Cornish DB & Clarke RV 2003. Opportunities, precipitators and criminal decisions: A reply to Wortley’s critique of situational crime prevention. In MJ Smith & DB Cornish (eds), Theory and practice in situational crime prevention. Monsey, NY: Criminal Justice Press: 41–96
Europol 2019. Internet organised crime threat assessment 2019. https://www.europol.europa.eu/activities-services/main-reports/internet…
*Gangwar A, Fidalgo E, Alegre E & González-Castro V 2017. Pornography and child sexual abuse detection in image and video: A comparative evaluation. Paper presented at the 8th International Conference on Imaging for Crime Detection and Prevention, Madrid, Spain: 37–42
*Hill K 2020. Unmasking a company that wants to unmask us all. New York Times, 20 January. https://www.nytimes.com/2020/01/20/reader-center/insider-clearview-ai.h…
*Hill K & Dance G 2020. Clearview’s facial recognition app is identifying child victims of abuse. New York Times, 7 February. https://www.nytimes.com/2020/02/07/business/clearview-facial-recognitio…
Huisman W & van Erp J 2013. Opportunities for environmental crime: A test of situational crime prevention theory. British Journal of Criminology 53(6): 1178–1200. https://doi.org/10.1093/bjc/azt036
*Hurley R, Prusty S, Soroush H, Walls R, Albrecht J, Cecchet E, Levine BN, Liberatore M, Lynn B & Wolak J 2015. Measurement and analysis of child pornography trafficking on P2P networks. https://ojjdp.ojp.gov/library/publications/measurement-and-analysis-chi…
Hutchinson A 2018. Facebook outlines enhanced efforts to remove child exploitation content from its platform. Social Media Today, 25 October. https://www.socialmediatoday.com/news/facebook-outlines-enhanced-effort…
International Centre for Missing and Exploited Children 2018. GMCNgine: Revolutionizing the search for missing children. https://plussocialgood.medium.com/gmcngine-revolutionizing-the-search-f…
*Joffres K, Bouchard M, Frank R & Westlake B 2011. Strategies to disrupt online child pornography networks. European Intelligence and Security Informatics Conference, Atlanta, Greece: 163–170
Johnson B & Patel P 2019. Multi-million pound funding to protect child abuse victims and track down offenders. https://www.gov.uk/government/news/multi-million-pound-funding-to-prote…
*Kashmir H 2020. Meet Clearview AI, the secretive company that might end privacy as we know it. Chicago Tribune, 18 January. https://www.chicagotribune.com/nation-world/ct-nw-nyt-clearview-facial-…
Microsoft 2020a. PhotoDNA. https://www.microsoft.com/en-us/photodna
Microsoft 2020b. PhotoDNA: FAQ. https://www.microsoft.com/en-us/photodna/faq
Mirage News 2020. 19-year-old charged with multiple child abuse offences. Mirage News, 30 June. https://www.miragenews.com/19-year-old-charged-with-multiple-child-abus…
National Center for Missing and Exploited Children 2020. NCMEC Data. https://www.missingkids.org/ourwork/ncmecdata
Oxford T 2019. I can see you. Linux Format, June. https://www.linuxformat.com/archives?issue=250
*Peersman C, Schulze C, Rashid A, Brennan M & Fischer C 2016. iCOP: Live forensics to reveal previously unknown criminal media on P2P networks. Digital Investigation 18: 50–64. https://doi.org/10.1016/j.diin.2016.07.002
*Peersman C, Schulze C, Rashid A, Brennan M & Fischer C 2014. iCOP: Automatically identifying new child abuse media in P2P networks. IEEE Security and Privacy Workshops. San Jose, CA: 124–131. https://ieeexplore.ieee.org/document/6957295
*Penna K, Clark A & Mohay G 2005. Challenges of automating the detection of paedophile activity on the internet. First International Workshop on Systematic Approaches to Digital Forensic Engineering. Washington, DC: 206–220
*Prichard J, Krone T, Spiranovic C & Watters P 2019. Transdisciplinary research in virtual space: Can online warning messages reduce engagement with child exploitation material? In R Wortley, A Sidebottom, N Tilley & G Laycock (eds), Routledge handbook of crime science. UK: Routledge: 309–19
*Prichard J, Watters P & Spiranovic C 2011. Internet subcultures and pathways to the use of child pornography. Computer Law & Security Review 27(6): 585–600
Prichard J, Wortley R, Watters P, Spiranovic C, Hunn C & Krone T 2021. Effects of automated messages on internet users attempting to access “barely legal” pornography. Sexual Abuse. Advance online publication. https://doi.org/10.1177/10790632211013809
Rayment-McHugh S, McKillop N & Christensen LS forthcoming. Educational and therapeutic programs that combat child sexual abuse material: A research synthesis
*Russell A 2020. RCMP used Clearview AI facial recognition tool in 15 child exploitation cases, helped rescue 2 kids. Global News, 27 February. https://globalnews.ca/news/6605675/rcmp-used-clearview-ai-child-exploit…
*Schell BH, Martin MV, Hung PCK & Rueda L 2007. Cyber child pornography: A review paper of the social and legal issues and remedies—and a proposed technological solution. Aggression and Violent Behavior 12(1): 45–63. https://doi.org/10.1016/j.avb.2006.03.003
*Schulze C, Henter D, Borth D & Dengel A 2014. Automatic detection of CSA media by multi-modal feature fusion for law enforcement support. In Proceedings of International Conference on Multimedia Retrieval. Glasgow, United Kingdom: 353–360
Seto MC 2013. Internet sex offenders. Washington, DC: American Psychological Association
Smallbone S, Marshall W & Wortley R 2008. Preventing child sexual abuse: Evidence, policy and practice. Devon UK: Willan Publishing
*Smallbone S & Wortley R 2017. Preventing child sexual abuse online. In J Brown (ed), Online risk to children: Impact, protection and prevention. London: Wiley: 143–162
United Nations Office on Drugs and Crime (UNODC) 2015. Study on the effects of new information technologies on the abuse and exploitation of children. Vienna: UNODC. https://www.unodc.org/documents/organized-crime/cybercrime/Study_on_the…
*Westlake B, Bouchard M & Frank R 2012. Comparing methods for detecting child exploitation content online. European Intelligence and Security Informatics Conference. Odense, Denmark: 156–63
*Williams KS 2005. Facilitating safer choices: Use of warnings to dissuade viewing of pornography on the internet. Child Abuse Review 14(6): 415–429. https://doi.org/10.1002/car.920
*Wolak J, Liberatore M & Levine BN 2014. Measuring a year of child pornography trafficking by U.S. computers on a peer-to-peer network. Child Abuse & Neglect 38(2): 347–56. https://doi.org/10.1016/j.chiabu.2013.10.018
Wortley R & Smallbone S 2012. Internet child pornography: Causes, investigation, and prevention. Global crime and justice series. Santa Barbara, CA: Praeger
Wortley R & Smallbone S 2006. Applying situational principles to sexual offenses against children. In R Wortley & S Smallbone (eds), Situational prevention of child sexual abuse. Monsey, NY: Criminal Justice Press: 7−36