Federico Matteo Benčić

Martin Perešíni, Federico Matteo Benčić, Kamil Malinka et al.

In response to the bottleneck of processing throughput inherent to single chain PoW blockchains, several proposals have substituted a single chain for Directed Acyclic Graphs (DAGs). In this work, we investigate two notable DAG-oriented designs. We focus on PHANTOM (and its optimization GHOSTDAG), which proposes a custom transaction selection strategy that enables to increase the throughput of the network. However, the related work lacks a thorough investigation of corner cases that deviate from the protocol in terms of transaction selection strategy. Therefore, we build a custom simulator that extends open source simulation tools to support multiple chains and enables us to investigate such corner cases. Our experiments show that malicious actors who diverge from the proposed transaction selection strategy make more profit as compared to honest miners. Moreover, they have a detrimental effect on the processing throughput of the PHANTOM (and GHOSTDAG) due to same transactions being included in more than one block of different chains. Finally, we show that multiple miners not following the transaction selection strategy are incentivized to create a shared mining pool instead of mining independently, which has a negative impact on decentralization.

Federico Matteo Benčić, Ivana Podnar Žarko

A new node joining a blockchain network first synchronizes with the network to verify ledger state by downloading the entire ledger history. We present Aurora, a probabilistic algorithm that \textit{identifies honest nodes} for transient or persistent communication in the presence of malicious nodes in a blockchain network, or ceases operation if it is unable to do so. The algorithm allows a node joining the network to make an informed decision about its next synchronization step or to verify that a transaction is contained in a valid ledger block without downloading the entire ledger or even the header chain. The algorithm constructs a Directed Acyclic Graph on the network topology to select a subset of nodes including a predefined number of honest nodes with a given probability. It is evaluated on a Bitcoin-like network topology using an open-source blockchain simulator. We investigate algorithm performance and analyze its communication complexity. Our results show that the algorithm facilitates trustless interactions of resource-constrained nodes with a blockchain network containing malicious nodes to enable a leaner initial blockchain download or an efficient and trustless transaction inclusion verification. Moreover, the algorithm can be implemented without any changes to the existing consensus protocol.