Shichen Wu (1. School of Cyber Science and Technology, Shandong University 2. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Puwen Wei (1. School of Cyber Science and Technology, Shandong University 2. Quancheng Laboratory 3. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Ren Zhang (Cryptape Co. Ltd. and Nervos), Bowen Jiang (1. School of Cyber Science and Technology, Shandong University 2. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education)

Proof-of-work (PoW) blockchain protocols based on directed acyclic graphs (DAGs) have demonstrated superior transaction confirmation performance compared to their chain-based predecessors. However, it is uncertain whether their security deteriorates in high-throughput settings similar to their predecessors, because their acceptance of simultaneous blocks and complex block dependencies presents challenges for rigorous security analysis.

We address these challenges by analyzing DAG-based protocols via a congestible blockchain model (CBM), a general model that allows case-by-case upper bounds on the block propagation delay, rather than a uniform upper bound as in most previous analyses. CBM allows us to capture two key phenomena of high-throughput settings: (1) simultaneous blocks increase each other's propagation delay, and (2) a block can be processed only after receiving all the blocks it refers to. We further devise a reasonable adversarial block propagation strategy in CBM, called the late-predecessor attack, which exploits block dependencies to delay the processing of honest blocks. We then evaluate the security and performance of Prism and OHIE, two DAG-based protocols that aim to break the security-performance tradeoff, in the presence of an attacker capable of launching the late predecessor attack. Our results show that these protocols suffer from reduced security and extended latency in high-throughput settings similar to their chain-based predecessors.

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Liheng Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Institute for Network Science and Cyberspace of Tsinghua University), Zheming Li (Institute for Network Science and Cyberspace of Tsinghua University), Zheyu Ma (Institute for Network Science and Cyberspace of Tsinghua University), Yuan Li (Tsinghua University),…

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Ke Mu (Southern University of Science and Technology, China), Bo Yin (Changsha University of Science and Technology, China), Alia Asheralieva (Loughborough University, UK), Xuetao Wei (Southern University of Science and Technology, China & Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, SUSTech, China)

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