Comparing Methods for Detecting Child Exploitation Content Online

The sexual exploitation of children online is seen as a global issue and has been addressed by both governments and private organizations. Efforts thus far have focused primarily on the use of image hash value databases to find content. However, recently researchers have begun to use keywords as a way to detect child exploitation content. Within the current study we explore both of these methodologies. Using a custom designed web-crawler, we create three networks using the hash value method, keywords method, and a hybrid method combining the first two. Results first show that the three million images found in our hash value database were not common enough on public websites for the hash value method to produce meaningful result. Second, the small sample of websites that were found to contain those images had little to no videos posted, suggesting a need for different criteria for finding each type of material. Third, websites with code words commonly known to be used by child pornographers to identify or discuss exploitative content, were found to be much larger than others, with extensive visual and textual content. Finally, boy-centered keywords were more commonly found on child exploitation websites than girl-centered keywords, though not at a statistically significant level. Applications for law enforcement and areas for future research are discussed

Validation of the Commercial Sexual Exploitation-Identification Tool

Trafficked youth are typically not identified until years after their exploitation has begun. In order to protect youth from prolonged abuse and violence and get them help, exploitation must be recognized as early as possible. To make this possible, service providers and other professionals who work with youth need a validated screening tool to aid in accurately detecting exploitation.the cse-it is an evidence based toolIn 2014, WestCoast Children's Clinic developed the Commercial Sexual Exploitation – Identification Tool (CSE-IT) with the input of over 100 survivors and service providers. In 2016, we validated the CSE-IT with data from a 15-month pilot to ensure that it accurately identifies youth who have clear indicators of exploitation. Since 2015 we have worked collaboratively with 77 agencies in 3 states to use the CSE-IT. As of June 2017, WestCoast has trained 4,000 service providers to recognize the signs of exploitation. These providers screened 12,500 youth and identified 1,500 youth with clear indicators of exploitation

Multimodal estimation of distribution algorithms

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima

Criminal Careers in Cyberspace: Examining Website Failure within Child Exploitation Networks

Publically accessible, illegal, websites represent an additional challenge for control agencies, but also an opportunity for researchers to monitor, in real time, changes in criminal careers. Using a repeated measures design, we examine evolution in the networks that form around child exploitation (CE) websites, over a period of 60 weeks, and determine which criminal career dimensions predict website failure. Network data were collected using a custom-designed web-crawler. Baseline survival rates were compared to networks surrounding (legal) sexuality and sports websites. Websites containing CE material were no more likely to fail than comparisons. Cox regression analyses suggest that increased volumes of CE code words and images are associated with premature failure. Websites that are more popular have higher odds of survival. We show that traditional criminal career dimensions can be transferred to the context of online CE and constitute some of the key determinants of an interrupted career

Investigation, Detection and Prevention of Online Child Sexual Abuse Material: A Comprehensive Survey

Child sexual abuse inflicts lifelong devastating consequences for victims and is a growing social concern. In most countries, child sexual abuse material (CSAM) distribution is illegal. As a result, there are many research papers in the literature which proposed technologies to detect and investigate CSAM. In this survey, a comprehensive search of the peer reviewed journal and conference paper databases (including preprints) is conducted to identify high-quality literature. We use the PRISMA methodology to refine our search space to 2,761 papers published by Springer, Elsevier, IEEE and ACM. After iterative reviews of title, abstract and full text for relevance to our topics, 43 papers are included for full review. Our paper provides a comprehensive synthesis about the tasks of the current research and how the papers use techniques and dataset to solve their tasks and evaluate their models. To the best of our knowledge, we are the first to focus exclusively on online CSAM detection and prevention with no geographic boundaries, and the first survey to review papers published after 2018. It can be used by researchers to identify gaps in knowledge and relevant publicly available datasets that may be useful for their research

A systematic survey of online data mining technology intended for law enforcement

As an increasing amount of crime takes on a digital aspect, law enforcement bodies must tackle an online environment generating huge volumes of data. With manual inspections becoming increasingly infeasible, law enforcement bodies are optimising online investigations through data-mining technologies. Such technologies must be well designed and rigorously grounded, yet no survey of the online data-mining literature exists which examines their techniques, applications and rigour. This article remedies this gap through a systematic mapping study describing online data-mining literature which visibly targets law enforcement applications, using evidence-based practices in survey making to produce a replicable analysis which can be methodologically examined for deficiencies

Disrupting Illicit Supply Networks: New Applications of Operations Research and Data Analytics to End Modern Slavery

Report from a 2017 National Science Foundation workshop on promising research directions for applications of operations research and data analytics toward the disruption of illicit supply networks like human trafficking. The workshop was funded by the NSF’s Operations Engineering (ENG) and the Law & Social Sciences Program (SBE) under grant # CMMI-1726895. The report addresses the opportunity to apply advances from the fields of operations research, management science, analytics, machine learning, and data science toward the development of disruptive interventions against illicit networks. Such an extension of the current research agenda for trafficking would move understanding of such dynamic systems from descriptive characterization and predictive estimation toward improved dynamic operational control.Bureau of Business Researc

Forensic science in combat of human trafficking

Although Forensic Science has become a crucial part of the investigation of many types of crime, the low number of scientific publications on the usage of Forensic Science to eliminate Human Trafficking or to speed up crime investigation, has given rise to the idea of conducting research on the role of Forensic Science in the investigation of Human Trafficking cases. The following literature review aims at judging the current importance of Forensic Science in solving and preventing Human Trafficking cases, at gathering ideas for the introduction of novel techniques and at identifying gaps of research within this field. For this purpose, a wider view, also addressing socio-economic topics, was applied

Finding the Key Players in Online Child Exploitation Networks

The growth of the Internet has been paralleled with a similar growth in online child exploitation. Since completely shutting down child exploitation websites is difficult (or arguably impossible), the goal must be to find the most efficient way of identifying the key targets and then to apprehend them. Traditionally, online investigations have been manual and centered on images. However, we argue that target prioritization needs to take more than just images into consideration, and that the investigating process needs to become more systematic. Drawing from a web crawler we specifically designed for extracting child exploitation website networks, this study 1) examines the structure of ten child exploitation networks and compares it to a control group of sports-related websites, and 2) provides a measure (network capital) that allows for identifying the most important targets for law enforcement purposes among our sample of websites. Results show that network capital — a combination between severity of content (images, videos, and text) and connectivity (links to other websites) — is a more reliable measure of target prioritization than more traditional measures of network centrality taken alone. Policy implications are discussed