Human Trafficking & Big Data

Introduction

Forcing a female to work as sex worker or forcing someone to do labor work with little or no pay at all, are problems that don't just exist in undeveloped poor countries; such heinous crimes take place everywhere in the world including rich developed western countries such as Canada and United States. Developed countries have more than enough resources to combat human right crimes such as human trafficking. In Canada human trafficking is not limited to border crossing where someone is trafficked from a foreign country; it also takes place domestically within Canada victims are victimized. In this blog I will share with you what is human trafficking and who are the victims? Examples of domestic human trafficking, What is big date and how can it be used to fight human trafficking, what are some of the data mining techniques that can be used to fight human trafficking and what are some of the challenges with big date?

What Is Human Trafficking & Who Are The Victims?

Human trafficking involves recruiting, moving or holding the victims to exploit them for most commonly two reasons: Force them to work as sex worker or forced labor. Victims are controlled by force or threats. Men also become victims. For instance coming to Canada legally after applying for an online job add. After arriving the host makes him work for extended hours, doesn’t pay, provides unsafe living conditions and threatens to call the police. In such cases language barriers and not knowing their rights play a significant role to continuously getting abused.

Human trafficking is defined as the, “recruitment, harboring, transportation, provision or objecting of a person for one of 3 purposes: 1) Labor of services, through the use of force, fraud, or coercion for the purpose of subjection to involuntary servitude, peonage, debt, bondage, or slavery , 2) commercial sex act though the use of force, fraud, or coercion, 3) Any commercial sex act of the person who is younger than 18 years, regardless of whatever any form of coercion is involved ”. 

Examples Of Domestic Human Trafficking

In Canada most of the reported cases of human trafficking were in Ontario and most of the victims were women or young girls. The people who become victims of human trafficking are those who are in tough or challenging situations such as desperate need of money, survival of abuse or don’t have a guardian/ family or don’t have any contacts with family.  For example a young female living with an abusive boyfriend who forces her to provide sexual services to clients in hotel and then hand over the earned money to him. Another example can be a young female who leaves home after having conflicts with her parents/ parent and moves in with an individual(s) who she trusted; those individual(s) later drug her and force her to provide sexual services and hand over the money to them.

What Is Big Data & How Can It be Used To Fight Human Trafficking 

Gathering information to fight a specific crime is not limited to traditional ways i.e. police reports because crimes are not limited to streets anymore. Criminals not only use technology to commit crimes but to also evade from punishment. Big data can be used as a solution to prevent significant human rights crime such as human trafficking. 

The most accepted definition of the big data is, “Big Data is the information asset characterized by such a high volume, velocity, and variety”. Big data is popular since 1993, when the first Optical Character Recognition (OCR) tool was lunched to create the “mass digitalization” project. The purpose of the project was to convert entire traditional libraries into machine readable files. It’s the information which are fundamental and makes the data, big data. In the present time, with frequent use of technology, big data is being created extensively in form of unstructured information i.e. texts, pictures, and videos. When it comes to human trafficking, organized crimes often use internet as a tool to target victims i.e. via online job advertisements.

 Data Mining Techniques To Prevent Human Trafficking

Some countries such as United States, passed laws which blocks the classified advertising sites i.e. backpage.com. Such laws create problem for everyday users of the internet who have nothing to do with human trafficking or sex work at all. A better approach will be to have a better understanding of cybercrimes. Cybercrimes are sometimes understood as crimes which can take place anywhere because they have no physical location which is a poor understanding; there is always a physical location where the victims are victimized. Various data mining techniques such as entity extract, cluster analysis, association rule, classification techniques, and social network analysis can help capture the physical location and analyze big data. 

Entity extraction is a technique which uses the software such as SPSS lexiQuest to extract valuable information especially from unstructured data i.e. in form of text. It is used to extract information from police reports but same technique can be used to extract information from big data. Cluster Analysis can be another example, it not only detects the crime hot spots by using Geographical Information System but also automatically identifies the existing crime data and all possible strongest association with related entities. To link all crime incidents, narrow down possible suspects and to discover new crime pattern, association rule is a helpful tool. Furthermore, in a larger size of data, classification techniques can be used to classify observations based on some significant rules/ attributes that are discovered from the database.

 Finally, social network analysis (SNA) can detect and illustrate relationship of individuals, groups, and events in a crime domain. It also identifies the key members and integration patterns between subgroups in criminal networks, as well as depict the suspects and their connections to other individuals or artifacts such as phone numbers and bank account. Human trafficking is a 150million dollar per year crime industry. SNA can show promising results to distinguish between a regular account and an account created for criminal purposes.

Big Data & It's Challenges

Since the data is extensively growing, an average IT system may not be very helpful when it comes to transformation networks. To store big data on a small device can be another significant problem. Efficient computer are required to transfer the data.