The United Nations defines human trafficking as the recruitment, transportation, transfer, harboring, or receipt of people through force, fraud, or deception, with the aim of exploiting them for profit. Human trafficking encompasses several crimes, including child sex trafficking, forced labor, domestic servitude, debt bondage, organ trafficking, and use as child soldiers. The number of victims is estimated at 40m worldwide, of which 81% are forced laborers, 25% are children, and 75% are women and girls with 55 different nationalities and hailing from 5 continents.

When investigating human trafficking, authorities are faced with a number of obstacles. First of all, investigators often lack resources and are under tremendous time pressure since the threat actors move their victims, resources, and payments quickly across several jurisdictions. Due to the fragmented nature of this crime, authorities, and investigators also have to deal with various cultures and overcome language barriers. Last but not least, human trafficking has gone digital and dark.

They use the dark web for their three main activities: the grooming and recruitment of victims, the advertisement of their illegal services, and the payment for their business expenses and services. They use digital technologies such as mobile phones and social networking sites on the dark web to remain anonymous. The widespread use of non-standard protocols, anonymous IP address allocation, and extensions of peer-to-peer content sharing on the dark web helps to mask criminal activities. The dark web is also used for payments for payment for illicit services using cryptocurrency, which ensures the anonymity of the payer and the payee.

For the last decade, law enforcement agencies have been trying to find ways how to stop human traffickers by using digital technology and the internet. Specialized cybercrime units and human trafficking task forces are cooperating more and more across state lines and borders to stop human trafficking. Traditionally, finding a missing person would involve manually combing through thousands, if not millions, of e.g., online ads on adult services websites to see if any of the posted images or information is useful. Such a process is time-consuming and tiring and prone to human error. It is too complicated to find the best answer to how to find human traffickers.

That’s why authorities are using advanced artificial intelligence algorithms and big data tools to scour all levels of the internet, including the dark web, to carry out human trafficking investigations and identify and catch traffickers. AI-based web intelligence tools are ideally suited to detect human traffickers to stop them and fight organized crime. An AI tool is designed to handle unstructured data, which is not presented in any of the familiar digital formats.

For instance, an AI tool can quickly and effectively sift through millions of online ads on e.g., commercial adult services websites based on specific search terms and phrases. This enables investigators to concentrate on other activities such as the dismantling of the crime network. Since a law enforcement agency is bound by the jurisdiction it operates in, an AI tool also allows its investigators to get a global view. The tool’s NLP algorithms help investigators to overcome the language barrier.

Traffickers will continue to innovate and find new and better ways to evade law enforcement, particularly via human trafficking on the dark web. Using an AI-powered WEBINT platform, such as Cobwebs, is the best way to identify human traffickers in the fight to stamp out and prevent human trafficking.