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