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Robustness of the Tangle 2.0 Consensus

[Seminar Series Spring ’23]



In this presentation, I will share the investigation results of the performance of the Tangle 2.0 consensus protocol in a Byzantine environment, which are published in the paper. We use an agent-based simulation model that incorporates the main features of the Tangle 2.0 consensus protocol. Our experimental results demonstrate that the Tangle 2.0 protocol is robust to the bait-and-switch attack up to the theoretical upper bound of the adversary’s 33% voting weight. We further show that the common coin mechanism in Tangle 2.0 is necessary for robustness against powerful adversaries. Moreover, the experimental results confirm that the protocol can achieve around 1s confirmation time in typical scenarios and that the confirmation times of non-conflicting transactions are not affected by the presence of conflicts.


Dr. Bing-Yang Lin

Dr. Bing-Yang Lin’s areas of expertise include data science, data analytics, machine learning, semiconductor testing, and blockchain consensus mechanisms. For a decade he has worked for some of the world’s leading companies, including TSMC and MTK. He joined IOTA in 2019, and is a Senior Research Engineer in IOTA foundation. He also is a prolific author, with nearly two-dozen papers published in IEEE conferences and industry journals. He holds a Ph.D in Electrical Engineering from National Tsing Hua University.