Thorn Uses AWS to Help Law Enforcement Identify Child-Trafficking Victims Faster
Easy communication at scale, disposable "burner" phones, and simple photo-editing tools— these are just some of the ways the digital, connected world was helping traffickers operate anonymously, one step ahead of the law—especially those who traffic children for sex online.
Then came a product called Spotlight.
"Abusers had figured out how to use advanced technology to facilitate their exploitation of children," says Sarah Potts, the head of marketing and communications for Thorn, the California-based nonprofit that created Spotlight. Thorn was founded in 2012 by Ashton Kutcher and Demi Moore to combat online child abuse. Potts adds, "We built Spotlight because we wanted to use advanced technology to help law enforcement turn the tables and find these children faster."
Spotlight's sophisticated machine-learning capabilities save time for overworked, under-resourced investigators by automatically flagging ads likely to represent at-risk children and keeping law enforcement agents from getting lost in a sea of online data. The app does this on a serverless Amazon Web Services (AWS) architecture that includes Amazon Rekognition, a deep learning–based image and video analysis service, and Amazon Elastic Compute Cloud (Amazon EC2) C5 instances. Powered by 3.0 GHz Intel Xeon Scalable processors, Amazon EC2 C5 instances offer a memory-to-vCPU ratio that is ideal for demanding inference applications.
“Spotlight helps officers identify child sex-trafficking ads much faster than the old paper-and-pencil methods.”
Brooke Istook, Director of Strategy and Operations, Thorn
AWS Services Used
Thorn was founded in 2012 to build technology to defend children from sexual abuse. The organization collaborates with law enforcement agencies, tech companies, and nonprofits. A virtual team based in the U.S., Thorn employs 25 people.
- Opened 21,000 trafficking cases
- Closes trafficking investigations faster
- Identified 18,000 victims, including over 6,000 children
AWS Services Used
Answering the Challenge Using AWS
A 2012 Thorn survey of child sex-trafficking survivors found that 75 percent had been sold online, most of them through escort websites. One way for law enforcement agents to catch traffickers and rescue kids would be to identify and investigate escort ads that seem to feature minors, but there are many obstacles to doing this.
One of the most significant obstacles is the massive volume of these ads. As Thorn started work on a tool that could help investigators identify children being exploited, more than 150,000 new escort ads were being posted online every day in the United States. Problems of scale like this cry out for automated processes, but another big obstacle is the fact that escort ad data is anything but consistent: traffickers use code words, slang, and reused content to complicate detection by machines.
To help investigators overcome these and other hurdles, Thorn collaborated with AWS and Digital Reasoning, a company specializing in cognitive-computing solutions, to build Spotlight. Spotlight's machine-learning models analyze new escort ads in real time and use intelligent image analysis and natural-language processing (NLP) to flag those that match risk profiles developed in cooperation with law enforcement agencies. Officers can set customized alerts and search Spotlight’s constantly growing database of ads to aid in their investigations.
Accelerating Victim Identification
Spotlight’s analytics pipeline begins with a third-party solution that ingests more than 100,000 new online escort ads each day, storing text and image data as objects in Amazon Simple Storage Service (Amazon S3) buckets. AWS Lambda functions orchestrate Amazon Simple Queueing Service (Amazon SQS) to queue new ads for processing by the app's analytics engine, Digital Reasoning Synthesys. The solution uses Amazon Simple Notification Service (Amazon SNS) to send alerts to law enforcement agents.
Spotlight's machine-learning models are trained and run on Amazon EC2 C5 instances. Powered by 3.0 GHz Intel Xeon Scalable processors, Amazon EC2 C5 instances offer a memory-to-vCPU ratio that is ideal for demanding inference applications. Spotlight, which is offered free of charge to law enforcement and allied organizations, uses Amazon Cognito to provide a secure user directory that can scale to millions of users.
Amazon Rekognition, which uses deep learning to accurately identify objects, people, activities, and events in images and videos stored in Amazon S3, is at the heart of one of Spotlight’s most crucial capabilities. Facial analysis in Amazon Rekognition helps investigators find photos of the same person that have been edited to defeat less intelligent image-search engines.
"We tested multiple facial-recognition services and found Amazon Rekognition was extremely accurate," says Kristin Boorse, the director of product management for Thorn. "It didn't make sense to build our own facial-recognition service when AWS already offers a best-in-breed solution like Amazon Rekognition. The Amazon Rekognition team has been very responsive in helping us address any challenges we encounter."
Finding Victims Faster
Since 2016 alone, Spotlight has helped officers in the United States and Canada open more than 21,000 trafficking cases and identify about 18,000 victims, including more than 6,000 children.
"Our law enforcement partners say Spotlight helps officers identify child sex-trafficking ads much faster than the old paper-and-pencil methods," says Brooke Istook, director of strategy and operations at Thorn. "With the flexibility and easy integration of AWS, we can experiment and prototype new products like Spotlight that would otherwise be cost-prohibitive to develop. On AWS, we can also respond to feature requests from officers in weeks or days—not a level of responsiveness public-sector agencies are used to seeing."
Combating online child sex trafficking is a team effort, according to Istook. " All of our technology partners are making crucial contributions to this fight. Spotlight could never have been so successful without substantial investment and support from AWS, or the underlying technologies that Intel has created.”