CSH-STATEMENT | New methods for investigating child sexual abuse


Jan 20, 2023

Child sexual abuse material is sold and traded via relevant platforms on the dark web. Payments are made through cryptocurrencies, usually Bitcoin. Currently, the number of cases is exploding. And current events clearly show how necessary it is to be able to track the payment flows in the trade of child pornography material.

 

The technology to do so is ready. Data scientist and crypto expert Bernhard Haslhofer from the Complexity Science Hub is working with his team to develop methods that make just that possible. Researchers are using these methods to analyze the enormous flood of data and thus unveil the financial flows in the context of child pornography. This allows them to uncover connections between child pornography platforms. Automated tracking of payment flows tracks down consumers who purchase such material on the one hand and the operators of such platforms themselves on the other.

 

These network analyses can support investigations by the authorities. Partnerships with Bavarian authorities are already showing initial success. Network analysis helps structure the increasing number of cases, enables targeted action, and enhances efficiency. “We live in the age of digitalization. Tomorrow will look different from today. This also affects cybercrime and child abuse in particular. For this reason, it is important that we think about methods today that we can also use tomorrow. Personally, I am pleased to be able to make a contribution here,” says Haslhofer.

 

Stefan Thurner, President of the Complexity Science Hub, also emphasizes: “Research in the digitalized world like this, where the analysis of huge amounts of data results in immediate benefits for the population – that is what we are committed to.”

For inquiries, please contact our press office:
Anja Böck, boeck@csh.ac.at, +43 1 59991 601

 

Further information and details on the first results of the cooperation with the ZCB will be presented at the press meeting at the Complexity Science Hub on January 31.


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