Speaker: Matthias Gusenbauer (ICGA)
This talk presents the topic of my master thesis at the computer graphic institute at TU Vienna. The thesis is a crossover of visualization with security and privacy. It proposes a combination of top-down and bottom-up approaches to solve the problem of visualizing the blockchain of crypto currencies. By reducing the amount of data to render and transmit, big data can be rendered on readily available hardware. In order to reduce data, hierarchical aggregation in combination with incremental data pre-loading was chosen.
The proposed solution is presented in the context of bitcoin, a financial network that uses a so-called blockchain as its core data storage. Due to the architecture of the bitcoin network, it is difficult to follow transferred money (bitcoin) from account to account. Due to pseudonymity many criminals have been using bitcoin as their choice of payment. Given recent developments with ransomware and the increased frequency of cyberattacks where bitcoin is used, being able to follow money-streams would help to combat cyber criminals. Bitcoin is a perfect example where explorative data visualization can help analysts solve the problem of not being able to follow the money. The public ledger that shows every transaction since the inception of bitcoin in 2009 is a suitable data set to test the feasibility of the proposed approach while also being recent and highly relevant in the domain of security.