@inproceedings{b9ae03603a00438182d8b999824b4a1f,
title = "WeRLman: To Tackle Whale (Transactions), Go Deep (RL)",
abstract = "Blockchain technology is responsible for the emergence of cryptocurrencies, such as Bitcoin and Ethereum. The security of a blockchain protocol relies on the incentives of its participants. Selfish mining is a form of deviation from the protocol where a participant can gain more than her fair share. Previous analyses of selfish mining make easing, non-realistic assumptions. We introduce a more realistic model with varying block rewards in the form of transaction fees. However, this comes at the cost of an intractable state space. To solve the complex model, we introduce WeRLman, a novel method based on deep Reinforcement Learning (deep RL). Using WeRLman, we show reward variability can significantly hurt blockchain security.",
keywords = "bitcoin, blockchain, deep Q networks, deep reinforcement learning, fees, security, selfish mining, transaction fees",
author = "Roi Bar-Zur and Ameer Abu-Hanna and Ittay Eyal and Aviv Tamar",
note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 15th ACM International Systems and Storage Conference, SYSTOR 2022 ; Conference date: 13-06-2022 Through 15-06-2022",
year = "2022",
month = jun,
day = "6",
doi = "10.1145/3534056.3535005",
language = "الإنجليزيّة",
series = "SYSTOR 2022 - Proceedings of the 15th ACM International Conference on Systems and Storage Conference",
pages = "148",
booktitle = "SYSTOR 2022 - Proceedings of the 15th ACM International Conference on Systems and Storage Conference",
}