Shi, HongweiWang, ShenglingHu, QinCheng, Xiuzhen2023-11-012023-11-012022-11-04Shi, H., Wang, S., Hu, Q., & Cheng, X. (2022). Black Swan in Blockchain: Micro Analysis of Natural Forking. IEEE Transactions on Dependable and Secure Computing, 1–13. https://doi.org/10.1109/TDSC.2022.3219443https://hdl.handle.net/1805/36833Natural forking is tantamount to the “black swan” event in blockchain since it emerges unexpectedly with a small probability, and may incur low resource utilization and costly economic loss. The ongoing literature analyzes natural forking mainly from the macroscopic perspective, which is insufficient to further understand this phenomenon since it roots in the instantaneous difference between block creation and propagation microscopically. Hence, in this paper, we fill this gap by leveraging the large deviation theory to conduct the first micro study of natural forking, aiming to reveal its inherent mechanism substantially. Our work is featured by 1) conceptual innovation . We creatively abstract the blockchain overlay network as a “service system”. This allows us to investigate natural forking from the perspective of “supply and demand”. Based on this, we can identify the competitive dynamics of blockchain and construct a queuing model to characterize natural forking; 2) progressiveness . We scrutinize the natural forking probability as well as its decay rate via a three-step scheme from simple to complex, which are the single-source i.i.d. scheme, the single-source non-i.i.d. scheme, and the many-source non-i.i.d. scheme. By doing so, we can answer when and how fast should we take actions and what actions should we take against natural forking. Our valuable findings can not only put forward decisive guidelines theoretically from the top level, but also engineer optimal countermeasures operationally on a practical level to thwart natural forking.enPublisher Policynatural forkingblockchainlarge deviation theoryqueuing theroryArticle