5,095 research outputs found
Short Paper: On Deployment of DNS-based Security Enhancements
Although the Domain Name System (DNS) was designed as a naming system, its
features have made it appealing to repurpose it for the deployment of novel
systems. One important class of such systems are security enhancements, and
this work sheds light on their deployment. We show the characteristics of these
solutions and measure reliability of DNS in these applications. We investigate
the compatibility of these solutions with the Tor network, signal necessary
changes, and report on surprising drawbacks in Tor's DNS resolution.Comment: Financial Cryptography and Data Security (FC) 201
Decentralization in Bitcoin and Ethereum Networks
Blockchain-based cryptocurrencies have demonstrated how to securely implement
traditionally centralized systems, such as currencies, in a decentralized
fashion. However, there have been few measurement studies on the level of
decentralization they achieve in practice. We present a measurement study on
various decentralization metrics of two of the leading cryptocurrencies with
the largest market capitalization and user base, Bitcoin and Ethereum. We
investigate the extent of decentralization by measuring the network resources
of nodes and the interconnection among them, the protocol requirements
affecting the operation of nodes, and the robustness of the two systems against
attacks. In particular, we adapted existing internet measurement techniques and
used the Falcon Relay Network as a novel measurement tool to obtain our data.
We discovered that neither Bitcoin nor Ethereum has strictly better properties
than the other. We also provide concrete suggestions for improving both
systems.Comment: Financial Cryptography and Data Security 201
Data mining for detecting Bitcoin Ponzi schemes
Soon after its introduction in 2009, Bitcoin has been adopted by
cyber-criminals, which rely on its pseudonymity to implement virtually
untraceable scams. One of the typical scams that operate on Bitcoin are the
so-called Ponzi schemes. These are fraudulent investments which repay users
with the funds invested by new users that join the scheme, and implode when it
is no longer possible to find new investments. Despite being illegal in many
countries, Ponzi schemes are now proliferating on Bitcoin, and they keep
alluring new victims, who are plundered of millions of dollars. We apply data
mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our
starting point is a dataset of features of real-world Ponzi schemes, that we
construct by analysing, on the Bitcoin blockchain, the transactions used to
perform the scams. We use this dataset to experiment with various machine
learning algorithms, and we assess their effectiveness through standard
validation protocols and performance metrics. The best of the classifiers we
have experimented can identify most of the Ponzi schemes in the dataset, with a
low number of false positives
Incentivising Privacy in Cryptocurrencies
Privacy was one of the key points mentioned in Nakamoto's Bitcoin whitepaper,
and one of the selling points of Bitcoin in its early stages. In hindsight,
however, de-anonymising Bitcoin users turned out to be more feasible than
expected. Since then, privacy focused cryptocurrencies such as Zcash and Monero
have surfaced. Both of these examples cannot be described as fully successful
in their aims, as recent research has shown. Incentives are integral to the
security of cryptocurrencies, so it is interesting to investigate whether they
could also be aligned with privacy goals. A lack of privacy often results from
low user counts, resulting in low anonymity sets. Could users be incentivised
to use the privacy preserving implementations of the systems they use? Not only
is Zcash much less used than Bitcoin (which it forked from), but most Zcash
transactions are simply transparent transactions, rather than the (at least
intended to be) privacy-preserving shielded transactions. This paper and poster
briefly discusses how incentives could be incorporated into systems like
cryptocurrencies with the aim of achieving privacy goals. We take Zcash as
example, but the ideas discussed could apply to other privacy-focused
cryptocurrencies. This work was presented as a poster at OPERANDI 2018, the
poster can be found within this short document
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