Tracking bitcoin users activity using community detection on a network of weak signals
This addresses the challenge of user anonymity in Bitcoin for researchers and security analysts, representing an incremental improvement over existing tracking methods.
The paper tackled the problem of tracking Bitcoin users by analyzing the transaction network, using community detection to re-identify multiple addresses belonging to the same user, demonstrating that this method can partially bypass Bitcoin's anonymity limitations.
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.