Erik Daniel

Erik Daniel, Florian Tschorsch

Due to their immutable log of information, blockchains can be considered as a transparency-enhancing technology. The immutability, however, also introduces threats and challenges with respect to privacy laws and illegal content. Introducing a certain degree of mutability, which enables the possibility to store and remove information, can therefore increase the opportunities for blockchains. In this paper, we present a concept for a mutable blockchain structure. Our approach enables the removal of certain blocks, while maintaining the blockchain's verifiability property. Since our concept is agnostic to any consensus algorithms, it can be implemented with permissioned and permissionless blockchains.

Fabian Stiehle, Erik Daniel, Florian Tschorsch

An important aspect of the propagation delay in blockchain networks is the block verification time, which is also responsible for the so-called verifier's dilemma. Models for the block verification time can help to understand and improve the verification process. Moreover, modeling the verification time is necessary for blockchain network simulations. In this paper, we present JOIST, a new model for the block verification time of Zcash. We identify computationally complex operations in the verification process of Zcash, and derive our model based on characteristic transaction features. We evaluate JOIST and show that the model is consistently more accurate than existing models, which consider the block size only.

Erik Daniel, Elias Rohrer, Florian Tschorsch

Zcash is a privacy-preserving cryptocurrency that provides anonymous monetary transactions. While Zcash's anonymity is part of a rigorous scientific discussion, information on the underlying peer-to-peer network are missing. In this paper, we provide the first long-term measurement study of the Zcash network to capture key metrics such as the network size and node distribution as well as deeper insights on the centralization of the network. Furthermore, we present an inference method based on a timing analysis of block arrivals that we use to determine interconnections of nodes. We evaluate and verify our method through simulations and real-world experiments, yielding a precision of 50 % with a recall of 82 % in the real-world scenario. By adjusting the parameters, the topology inference model is adaptable to the conditions found in other cryptocurrencies and therefore also contributes to the broader discussion of topology hiding in general.