1,576 research outputs found
A Flexible Network Approach to Privacy of Blockchain Transactions
For preserving privacy, blockchains can be equipped with dedicated mechanisms
to anonymize participants. However, these mechanism often take only the
abstraction layer of blockchains into account whereas observations of the
underlying network traffic can reveal the originator of a transaction request.
Previous solutions either provide topological privacy that can be broken by
attackers controlling a large number of nodes, or offer strong and
cryptographic privacy but are inefficient up to practical unusability. Further,
there is no flexible way to trade privacy against efficiency to adjust to
practical needs. We propose a novel approach that combines existing mechanisms
to have quantifiable and adjustable cryptographic privacy which is further
improved by augmented statistical measures that prevent frequent attacks with
lower resources. This approach achieves flexibility for privacy and efficency
requirements of different blockchain use cases.Comment: 6 pages, 2018 IEEE 38th International Conference on Distributed
Computing Systems (ICDCS
Network-based indicators of Bitcoin bubbles
The functioning of the cryptocurrency Bitcoin relies on the open availability
of the entire history of its transactions. This makes it a particularly
interesting socio-economic system to analyse from the point of view of network
science. Here we analyse the evolution of the network of Bitcoin transactions
between users. We achieve this by using the complete transaction history from
December 5th 2011 to December 23rd 2013. This period includes three bubbles
experienced by the Bitcoin price. In particular, we focus on the global and
local structural properties of the user network and their variation in relation
to the different period of price surge and decline. By analysing the temporal
variation of the heterogeneity of the connectivity patterns we gain insights on
the different mechanisms that take place during bubbles, and find that hubs
(i.e., the most connected nodes) had a fundamental role in triggering the burst
of the second bubble. Finally, we examine the local topological structures of
interactions between users, we discover that the relative frequency of triadic
interactions experiences a strong change before, during and after a bubble, and
suggest that the importance of the hubs grows during the bubble. These results
provide further evidence that the behaviour of the hubs during bubbles
significantly increases the systemic risk of the Bitcoin network, and discuss
the implications on public policy interventions
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