![]() So part of the higher price might reflect commuting time. “Why would that be? One hypothesis is that traveling takes time and money-you have to get in your car and go somewhere. “Sex workers charge more for out-calls across every city in the data set,” Cafarella explains. Take, for example, out-calls, when a sex worker travels to a client, and in-calls, when a sex worker stays in place and the client travels. The whole idea is based on economic rationality. Those sex workers may create a trail toward a human trafficker who’s actually making the rules and setting the price. “If we can understand the market and how and why people price, then we can look at a sex worker who’s much cheaper in her advertisement than you might expect, which suggests that the worker is not pricing her own services.” He says law enforcement can flag and prioritize such outliers who don’t follow expected economic incentives. “The goal is to understand economic models of how people do the pricing,” says Cafarella. Dark Web DiscountĬomputer code and web crawlers can’t, of course, perfectly translate the human reality captured in sex ad data. Another clue is the same phone number showing up in ads that switch locations frequently: Human traffickers disorient their victims by moving them from place to place, minimizing access to social ties and local resources, and making it tough for captives to escape. “So far, we’ve made the whole process of building a high-quality data set faster and easier.”Ī slew of phone numbers with consecutive final digits, listed in related sex ads, may indicate that someone bought a suspiciously large number of cell phones for the purpose. “Just like if a reader were being really fast and sloppy, they might skip over a lot of things,” he says.Ĭafarella’s work with collaborators has improved dark net search tools. Earlier methods missed important data, too. For example, it might interpret a 48103 zip code as the price $48,103. Earlier technology, Cafarella says, suffered from mistakes and imprecision. ![]() Ads for sex workers in the dark web contain price, location, and service details. The hard part of Cafarella’s work is information extraction. He’s analyzed something like 80 million sex ads so far, using automated methods like machine learning and image recognition to uncover who’s behind those shady business deals. “We’re trying to build data tools for addressing crime-in particular human trafficking-where the internet might provide a lot of data,” says Cafarella. Since 2014, Memex has focused on human trafficking not only because it’s a particularly grim industry, but also because money from the sex trade often funds other illegal activities, such as drugs and weapons. ![]() Memex uses search functions that sidestep the limitations of the text-based search engines that most of us use, making the dark web scrutable. Working with DARPA (the Department of Defense’s Advanced Research Projects Agency), Computer Science and Engineering Professor Mike Cafarella, who also teaches in LSA’s Computer Science Program, is bringing light to the dark web with a project called Memex. ![]()
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