Using Memex’s Domain-Specific Search Capabilities and Data to Reveal Clandestine Organ Trade

Duminda Wijesekera, Bo Yu, Michael HeinlGeorge Mason University

703-993-1530

Challenges

• The high global demand for human organs(especially kidneys)

• The availability of low-cost internet in developingcountries

• Hidden services and social media networks arealso used to illegally trade human organs

Roles, Actions in Organ Trafficking

Characterize the four main actors in organ trafficking as well as their motivations —

• Buyers: The ultimate buyers are most likely patients from richer countries suffering from diseases such as kidney insufficiency since insufficient supply of organs.

• Sellers / Donors: are often poor, young, male humans. The most motivations are making money (either autonomously or pushed by their social environment), or paying their own trafficking with an organ by young refugees.

• Brokers: are the central actors holding together the whole organ trafficking network and also the group financially benefiting the most.

• Transplant Surgeons: Although breaking legal and ethical standards, there are medical professionals who willingly transplant trafficked organs benefiting from the high prices payed for organs.

The key idea is to apply the forensic methodology provided by Mena with modified/combined the machine learning parts

Our Approach

Statistical Methods & Adopted Tools

Risk Model

Examples

The statistical approach used to combine information is usingBayesian Networks (BN) (Pearl, 1988) , which

• Is a graphical, flexible means of expressing joint probability distributionsover interrelated hypotheses

• allows the formal modeling and incorporation of multiple data sources into a complex assessment, and they also allow uncertainty quantification. Uncertainty quantification is important.

• Is an open-sourced software• Using component-oriented

design

unbbayes.evaluation: it contains classes for evaluating BN.unbbayes.io: it contains classes for storage. E.g. storing BN, configurations, preferences or logs as files.unbbayes.prs: it contains classes representing data structures and algorithms. Conceptual elements (e.g. Node, Edge, Network, JunctionTree, PotentialTable) and operations on them.

Revealing clandestine Organ Trade & evaluating risks associated with such action

It is illegal, but it is not stopped, Since…

“More than one human organ is illegally purchased every hour worldwide — the majority of these are kidneys” (World Health Organization, 2012)

(a) Seller Post in Moneybook

(b) Buyer Entry in Moneybook

• Understand the Investigation Objective: Define criteria andfinal outcomes of the analysis and generate initial indicators ofhuman organ trafficking with the assistance of subject-matterexperts in order to classify example data.

• Understand the Data: Find hidden services, crawl their data,filter and store it appropriately.

• Preparing the data: Bring the retrieved and filtered data in anappropriate structure for processing.

• Pick and evaluate an appropriate model: Find appropriatealgorithms for data processing and adjust parameters usingprovided reference data.

• Detection: Use the analyzed and clustered data to build apredictive risk model of illegal human organ trafficking.

Modeling SystemsWhere,

• If there is Disaster Areas (DA) and/or is War Zones (WZ) and/or is Barren Areas (BA), the people’s Living loCation (LC) will be Poor; Otherwise, if there is Affluent Areas, the people’s Living Location will be Good

• If people Living loCation (LC) is Poor, and Law Enforcement (LE) is Weak, there will be High Probabilities of Seeking the Kidneys (SK). Otherwise, there will be Low Probabilities of Seeking the Kidneys (SK) Note: For Chinese situation, will need add additional notes in the model.

• If a Health Person (HP) is Seeking Kidney (SK), who probably is Seeking Sell Kidney (SSK)

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