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(ICBC 2021) Alternative Difficulty Adjustment Algorithms for Preventing Selfish Mining Attack

About This Webinar

Abstract: Selfish mining is one of the most famous attacks on the mining process of Bitcoin and other Proof-of-Work blockchains in general. So, preventing selfish mining is an important objective. There have been a few attempts to prevent selfish mining. In this work, we focus on alternative difficulty adjustment algorithms that try to discourage selfish miners by extending their waiting time for selfish mining to become profitable, Zeno's DAA in particular. We propose two extensions on Zeno's DAA: 1) Zeno's Max DAA, which increase the difficulty in one step but decreases it in multiple steps, and 2) Zeno's Parametric DAA that has a parameter that can be tuned to control the rate of the decrement (or increment) in the value of difficulty. We evaluate these two alternatives DAAs and show that Zeno's Max performs better than Zeno's for scalability of the network and scales the network faster. Also, Zeno's Parametric is a family of DAAs that not only has the default DAA and Zeno's DAA as its members but also can include anything in between or even DAAs more conservative than Zeno's, which decrease the difficulty even slower than Zeno's.

Authors: Hamid Azimy and Ali A. Ghorbani (University of New Brunswick, Canada)

Email: hazimy@unb.ca, ghorbani@unb.ca

Who can view: Everyone
Webinar Price: Free
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