Improving Blockchain Consistency by Assigning Weights to Random Blocks

Qing Zhang, Xueping Gong, Huizhong Li, Hao Wu, Jiheng Zhang

Blockchains based on the celebrated Nakamoto consensus protocol have shown promise in several applications, including cryptocurrencies. However, these blockchains have inherent scalability limits caused by the protocol's consensus properties. In particular, the consistency property demonstrates a tight trade-off between block production speed and the system's security in terms of resisting adversarial attacks. This paper proposes a novel method, Ironclad, that improves blockchain consistency by assigning different weights to randomly selected blocks. We analyze the fundamental properties of our method and show that the combination of our method with Nakamoto consensus protocols can lead to significant improvement in consistency. A direct result is that Nakamoto+Ironclad can enable a much faster ($10\sim 50$ times with normal parameter settings) block production rate than Nakamoto protocol under the same security guarantee with the same proportion of malicious mining power.

Knowledge Graph



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