Abstract : Bitcoin is a cryptocurrency attracting a lot of interest both from the general public and researchers. There is an ongoing debate on the question of users' anonymity: while the Bitcoin protocol has been designed to ensure that the activity of individual users could not be tracked, some methods have been proposed to partially bypass this limitation. In this article, we show how the Bitcoin transaction network can be studied using complex networks analysis techniques, and in particular how community detection can be efficiently used to re-identify multiple addresses belonging to a same user.
Type de document :
Communication dans un congrès
The 6th International Conference on Complex Networks and Their Applications, Nov 2017, Lyon, France
https://hal.archives-ouvertes.fr/hal-01617992
Contributeur : Remy Cazabet
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Soumis le : mardi 17 octobre 2017 - 13:13:12
Dernière modification le : jeudi 7 février 2019 - 16:47:05
Document(s) archivé(s) le : jeudi 18 janvier 2018 - 14:07:25
Rémy Cazabet, Rim Baccour, Matthieu Latapy. Tracking bitcoin users activity using community detection on a network of weak signals. The 6th International Conference on Complex Networks and Their Applications, Nov 2017, Lyon, France. 〈hal-01617992〉
