Agenda

Speaker: Ivan Homoliak, Brno University of Technology, Czech Republic

Abstract:
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 in 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 the 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. Recently, we extended this work by game theoretic analysis that proves that selecting transactions with various fees randomly is not a Nash Equilibrium. Also, we made some simulation experiments with a real-world topology with 8000 nodes. One potential option is to design a DAG-base PoS protocol that will be resistant to mentioned problems. See our short paper https://ieeexplore.ieee.org/abstract/document/10411447 and full paper at https://arxiv.org/pdf/2305.16757.pdf. Also simulator that we designed at https://ui.adsabs.harvard.edu/abs/2023arXiv231104638P/abstract

Bio Sketch:
Ivan is assistant professor (awaiting assoc. professorship) at Brno University of Technology in Czech Republic and currently focuses on the research in various blockchain-based areas, such as 2nd layer ledgers, e-voting, CBDC, applied trusted comping, security & performance of consensus protocols, and system security in general. Before that, Ivan worked at SUTD on various projects focusing on the security of blockchains and insider threat detection. Ivan has a Ph.D. in the area of adversarial intrusion detection in network traffic from Brno University of Technology, Faculty of Information Technology (BUT FIT).