Personalized Difficulty Adjustment for Countering the Double-Spending Attack in Proof-of-Work Consensus Protocols
This addresses security vulnerabilities in decentralized cryptocurrencies like Bitcoin, though it appears incremental as it modifies existing difficulty adjustment rather than introducing a new paradigm.
The paper tackles the double-spending attack risk in Bitcoin's proof-of-work consensus by proposing a personalized difficulty adjustment mechanism that reduces the probability of consecutive block wins, resulting in a more trustworthy system.
Bitcoin is the first secure decentralized electronic currency system. However, it is known to be inefficient due to its proof-of-work (PoW) consensus algorithm and has the potential hazard of double spending. In this paper, we aim to reduce the probability of double spending by decreasing the probability of consecutive winning. We first formalize a PoW-based decentralized secure network model in order to present a quantitative analysis. Next, to resolve the risk of double spending, we propose the personalized difficulty adjustment (PDA) mechanism which modifies the difficulty of each participant such that those who win more blocks in the past few rounds have a smaller probability to win in the next round. To analyze the performance of the PDA mechanism, we observe that the system can be modeled by a high-order Markov chain. Finally, we show that PDA effectively decreases the probability of consecutive winning and results in a more trustworthy PoW-based system.