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Developing a safe and trusted collaboration environment to monitor and combat human trafficking

by: data-sharing-coalition|

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human trafficking

Developing a safe and trusted collaboration environment to monitor and combat human trafficking

Human trafficking is a growing global problem. The private, public, and civil sectors are coming under pressure to collaborate with each other to detect and disrupt the human trafficking business model. Each sector collects and uses information differently. Law enforcement authorities gain criminal insights from informants. The civil sector focuses on victim-centred accounts. The private sector focuses on suspicious transactions under regulatory compliance and slavery-free supply chains. Sharing data to create an integrated view of the modus operandi of traffickers is the next step in unlocking the value of data in the fight against human trafficking. However, creating a collaboration environment comes with data sharing challenges. Stakeholders face regulatory and trust barriers (e.g., identity revealed, legal complexity) that limit their willingness and ability to share data. The Data Sharing Coalition, participants Sustainable Rescue Foundation, Roseman Labs and Pinsent Masons, NGOs and other participants are answering these challenges in a use case to test the potential of an emerging technology: Multi-Party Computation (MPC). Secure MPC is a technology that enables data collaboration without parties sharing the actual data. Instead, MPC makes use of an algorithm that is sent to the respective data sources to generate relevant insights. This means that compliance with relevant legislation would be less complex and data collaboration would be easier. But more importantly, it could make human trafficking more visible.

Human trafficking is a worldwide societal problem that occurs in all sectors

Human trafficking involves the use of force, fraud, or coercion by traffickers to exploit people in labour, sex, and organ trafficking, domestic servitude, and forced criminality. Driving forces of vulnerability are social and economic inequality, poverty, and conflict. Potential victims can be of any age, race, gender, or nationality and are often controlled by violence, debt bondage, and withholding of documentation. An estimated 40 million people, including men, women, and children are trafficked worldwide – including here in the Netherlands. The number of victims of human trafficking in the Netherlands is nearly five times the reported estimate. More than 6,000 individuals fall victim to human trafficking each year with roughly two-thirds of cases involving coerced sexual exploitation. Labour traffickers in the Netherlands exploit adults from Eastern Europe, Africa, and South and East Asia in industries such as inland shipping, leisure river cruises, agriculture, horticulture, hospitality, domestic servitude, and forced criminal activity.

Protection of identities and data privacy is key in organising digital collaboration to combat human trafficking

Human trafficking is a predicative crime often associated with money laundering, fraud, and drugs. It is well-hidden in national and cross-border crimes and investigated by different parties (law enforcement agencies, NGOs, financial institutions). Each party has developed a solution, but few of the solutions support cross-domain collaboration. Data on traffickers and victims is ever-changing, difficult to obtain and often just a snapshot in time from a specific region. Involved parties could strengthen their knowledge positions by sharing relevant data, but face multiple barriers:

  • Legal complexity in sharing data due to various restrictions
  • Risk that sharing information could endanger informants’ lives
  • Risk that sharing data will break the trust relationships between NGOs and their clients

These data barriers result in partial and fragmented data that makes it difficult to piece together a robust understanding of the trafficking modus operandi in recruitment, transport and exploitation. A good example is interview information obtained by law enforcement agencies from victims of forced prostitution versus victim-centred stories obtained by NGOs from victims and sex workers. The goal for the participating NGOs, Roseman Labs, Sustainable Rescue Foundation, Pinsent Masons and other participants (i.e. consortium) is to develop a use case based on MPC technology, with additional trust and interoperability features, as a proof of concept to overcome these data sharing barriers.

Multi Party Computation (MPC) technology could act as the basis to provide security and trust in digital collaboration

MPC technology has a specific characteristic that will enable use case stakeholders to share their data on human trafficking in the sex industry without revealing the source data. Instead of sharing the data, authorities allow a transparent algorithm to query their data sources for specific entries shared through innovative cryptography. This mitigates the risks because no personal data is exposed and legal rights are protected.

MPC technology has large scalability potential in detecting and monitoring human trafficking

As a proof of concept, this use case serves as the foundation for secure data exchanges between different parties monitoring human trafficking and is expected to evolve into other use cases. For example, within sexual exploitation the use case can be expanded to include additional data sources (such as universities and financial institutions) linked with ongoing law enforcement investigations of forced prostitution in the Netherlands. Because the Netherlands is a source, transport and destination country, the use case could be further expanded with similar stakeholders in respective domains (NGOs, law enforcement) across borders to improve coherence and overall investigations. As the human trafficking data sharing ecosystem grows the potential to improve the information position of other themes in forced prostitution such as lover boy phenomena and exploitation can be addressed. As well as other types of exploitation in other sectors (e.g. organ trafficking, hospitality, agriculture, construction).

Are you interested in the use case and would you like to know more, or do you have an idea for a cross-domain data sharing use case? Please contact us