Investigating child sexual abuse material availability, searches, and users on the anonymous Tor network for a public health intervention strategy (2404.14112v1)
Abstract: Tor is widely used for staying anonymous online and accessing onion websites; unfortunately, Tor is popular for distributing and viewing illicit child sexual abuse material (CSAM). From 2018 to 2023, we analyse 176,683 onion domains and find that one-fifth share CSAM. We find that CSAM is easily available using 21 out of the 26 most-used Tor search engines. We analyse 110,133,715 search sessions from the Ahmia.fi search engine and discover that 11.1% seek CSAM. When searching CSAM by age, 40.5% search for 11-year-olds and younger; 11.0% for 12-year-olds; 8.2% for 13-year-olds; 11.6% for 14-year-olds; 10.9% for 15-year-olds; and 12.7% for 16-year-olds. We demonstrate accurate filtering for search engines, introduce intervention, show a questionnaire for CSAM users, and analyse 11,470 responses. 65.3% of CSAM users first saw the material when they were children themselves, and half of the respondents first saw the material accidentally, demonstrating the availability of CSAM. 48.1% want to stop using CSAM. Some seek help through Tor, and self-help websites are popular. Our survey finds commonalities between CSAM use and addiction. Help-seeking correlates with increasing viewing duration and frequency, depression, anxiety, self-harming thoughts, guilt, and shame. Yet, 73.9% of help seekers have not been able to receive it.
- Guitton, C. A review of the available content on Tor hidden services: The case against further development. \JournalTitleComputers in Human Behavior 29, 2805–2815, DOI: https://doi.org/10.1016/j.chb.2013.07.031 (2013).
- Perpetuating online sexism offline: Anonymity, interactivity, and the effects of sexist hashtags on social media. \JournalTitleComputers in Human Behavior 52, 436–442, DOI: https://doi.org/10.1016/j.chb.2015.06.024 (2015).
- Child pornography: An internet crime (Routledge, 2004).
- Online child pornography offenders are different: A meta-analysis of the characteristics of online and offline sex offenders against children. \JournalTitleArchives of sexual behavior 44, 45–66 (2015).
- https://doi.org/10.1176/appi.books.9780890425787.
- Motivational pathways underlying the onset and maintenance of viewing child pornography on the Internet. \JournalTitleBehavioral Sciences & the Law 38, 100–116 (2020).
- Problematic pornography use: Legal and health policy considerations. \JournalTitleCurrent Addiction Reports 1–12 (2021).
- Risk Factors for Child Sexual Abuse Material Users Contacting Children Online: Results of an Anonymous Multilingual Survey on the Dark Web. \JournalTitleJournal of Online Trust and Safety 1 (2022).
- Levine, B. N. Increasing the Efficacy of Investigations of Online Child Sexual Exploitation (2022). https://www.ojp.gov/library/publications/increasing-efficacy-investigations-online-child-sexual-exploitation-report.
- New Me: Understanding Expert and Non-Expert Perceptions and Usage of the Tor Anonymity Network. In Thirteenth Symposium on Usable Privacy and Security, SOUPS 2017, Santa Clara, CA, USA, July 12-14, 2017, 385–398 (USENIX Association, 2017).
- Towards Understanding Privacy and Trust in Online Reporting of Sexual Assault. In Lipford, H. R. & Chiasson, S. (eds.) Sixteenth Symposium on Usable Privacy and Security, SOUPS 2020, August 7-11, 2020, 145–164 (USENIX Association, 2020).
- Winter, P. et al. How Do Tor Users Interact With Onion Services? In Enck, W. & Felt, A. P. (eds.) 27th USENIX Security Symposium, USENIX Security 2018, Baltimore, MD, USA, August 15-17, 2018, 411–428 (USENIX Association, 2018).
- A Broad Evaluation of the Tor English Content Ecosystem. In Boldi, P. et al. (eds.) Proceedings of the 11th ACM Conference on Web Science, WebSci 2019, Boston, MA, USA, June 30 - July 03, 2019, 333–342, DOI: https://doi.org/10.1145/3292522.3326031 (ACM, 2019).
- The potential harms of the Tor anonymity network cluster disproportionately in free countries. \JournalTitleProceedings of the National Academy of Sciences 117, 31716–31721, DOI: https://doi.org/10.1073/pnas.2011893117 (2020).
- Aked, S. An investigation into darknets and the content available via anonymous peer-to-peer file sharing. \JournalTitle9th Australian Information Security Management Conference (2011).
- Drawing the web structure and content analysis beyond the Tor darknet: Freenet as a case of study. \JournalTitleJ. Inf. Secur. Appl. 68, 103229, DOI: https://doi.org/10.1016/j.jisa.2022.103229 (2022).
- Empirical analysis of Tor Hidden Services. \JournalTitleIET Information Security 10, 113–118, DOI: https://doi.org/10.1049/iet-ifs.2015.0121 (2016).
- Towards a Comprehensive Insight into the Thematic Organization of the Tor Hidden Services. In IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014, The Hague, The Netherlands, 24-26 September, 2014, 220–223, DOI: https://doi.org/10.1109/JISIC.2014.40 (IEEE, 2014).
- Criminal motivation on the dark web: A categorisation model for law enforcement. \JournalTitleDigit. Investig. 24, 62–71, DOI: https://doi.org/10.1016/j.diin.2017.12.003 (2018).
- Classification of illegal activities on the dark web. In Proceedings of the 2nd International Conference on Information Science and Systems, 73–78 (2019).
- Child sexual abuse and covid-19: Side effects of changed societies and positive lessons for prevention. \JournalTitleCriminal Behaviour and Mental Health 31, 289 (2021).
- Collecting and viewing behaviors of child sexual exploitation material offenders. \JournalTitleChild Abuse & Neglect 118, 105133 (2021).
- Blanchard, R. et al. Pedophilia, hebephilia, and the DSM-V. \JournalTitleArchives of sexual behavior 38, 335–350 (2009).
- Relative weight and race influence average age at menarche: results from two nationally representative surveys of us girls studied 25 years apart. \JournalTitlePediatrics 111, 844–850 (2003).
- Exposure to sexually explicit media in early adolescence is related to risky sexual behavior in emerging adulthood. \JournalTitlePloS one 15, e0230242 (2020).
- X-rated: Sexual attitudes and behaviors associated with US early adolescents’ exposure to sexually explicit media. \JournalTitleCommunication research 36, 129–151 (2009).
- Developmental pathways into social and sexual deviance. \JournalTitleJournal of Family Violence 25, 141–148 (2010).
- Adverse childhood experiences: What we know, what we don’t know, and what should happen next. \JournalTitleEarly intervention foundation 129 (2020).
- Beier, K. M. et al. Can pedophiles be reached for primary prevention of child sexual abuse? first results of the berlin prevention project dunkelfeld (ppd). \JournalTitleThe journal of forensic psychiatry & psychology 20, 851–867 (2009).
- The International Classification of Diseases 11th Revision (ICD-11) – 6C72 Compulsive sexual behaviour disorder (2022). https://icd.who.int/browse11/l-m/en#/http://id.who.int/icd/entity/1630268048.
- Cybersex addiction: Experienced sexual arousal when watching pornography and not real-life sexual contacts makes the difference. \JournalTitleJournal of behavioral addictions 2, 100–107 (2013).
- Model of problematic Internet use in people with a sexual interest in children. \JournalTitleCyberPsychology & Behavior 6, 93–106 (2003).
- Sex offenders, Internet child abuse images and emotional avoidance: The importance of values. \JournalTitleAggression and violent Behavior 11, 1–11 (2006).
- Obstacles to help-seeking for sexual offenders: Implications for prevention of sexual abuse. \JournalTitleJournal of child sexual abuse 26, 99–120 (2017).
- Outpatient therapists’ perspectives on working with persons who are sexually interested in minors. \JournalTitleArchives of sexual behavior 51, 4157–4178 (2022).
- “I can’t talk about that”: Stigma and fear as barriers to preventive services for minor-attracted persons. \JournalTitleStigma and Health 4, 400 (2019).
- The need for a comprehensive public health approach to preventing child sexual abuse (2014).
- Reasons for help-seeking and associated fears in subjects with substance dependence. \JournalTitleIndian journal of psychological medicine 34, 153–158 (2012).
- Privacy Worlds: Exploring Values and Design in the Development of the Tor Anonymity Network. \JournalTitleScience, Technology, & Human Values 47, 910–936, DOI: https://doi.org/10.1177/01622439211039019 (2022).
- Sardá, T. An onion with layers of hope and fear: A cross-case analysis of the media representation of Tor Network reflecting theoretical perspectives of new technologies. \JournalTitleSecurity and Privacy e296 (2023).
- ICMEC. Child Sexual Abuse Material: Model Legislation and Global Review. 9th Edition. (2018). https://www.icmec.org/child-pornography-model-legislation-report/.
- Clarke, R. V. Situational crime prevention. \JournalTitleCrime and justice 19, 91–150 (1995).
- Situational Crime Prevention (SCP) techniques to prevent and control cybercrimes: A focused systematic review. \JournalTitleComputers & Security 115, 102611, DOI: https://doi.org/10.1016/j.cose.2022.102611 (2022).
- Krone, T. et al. Child sexual abuse material in child-centred institutions: situational crime prevention approaches. \JournalTitleJournal of Sexual Aggression 26, 91–110, DOI: https://doi.org/10.1080/13552600.2019.1705925 (2020).
- Prichard, J. et al. Effects of automated messages on internet users attempting to access “barely legal” pornography. \JournalTitleSexual Abuse 34, 106–124 (2022).
- Lätth, J. et al. Effects of internet-delivered cognitive behavioral therapy on use of child sexual abuse material: A randomized placebo-controlled trial on the Darknet. \JournalTitleInternet Interventions 30, 100590, DOI: https://doi.org/10.1016/j.invent.2022.100590 (2022).
- Tor metrics – onion services (2023). The Tor Project. https://metrics.torproject.org/hidserv-dir-v3-onions-seen.html?start=2022-11-23&end=2023-01-03.
- Yu, B. An evaluation of text classification methods for literary study. \JournalTitleLit. Linguistic Comput. 23, 327–343, DOI: https://doi.org/10.1093/llc/fqn015 (2008).
- Comparison of Naive Bayes, Random Forest, Decision Tree, Support Vector Machines, and Logistic Regression Classifiers for Text Reviews Classification. \JournalTitleBalt. J. Mod. Comput. 5, DOI: https://doi.org/10.22364/bjmc.2017.5.2.05 (2017).