TY - GEN
T1 - Exploring Mining Pool Rewards in Zcash at a Deeper Level
AU - Wang, Xi
AU - Zhu, Liehuang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Zcash has attracted the attention of numerous users, including large mining pools, due to its excellent privacy protection and anonymity. The analysis of Zcash mining ecosystem contributes to understanding the evolution trend of cryptocurrency, evaluating system stability, and optimizing network governance. However, limited by the pseudonym mechanism and shielded pool of Zcash, there is little research on Zcash mining. Existing analysis of blockchain mining is limited to Bitcoin and Ethereum, where their methods are useless on Zcash with its enhanced privacy protection. To solve the above problems, this paper uses the block data of Zcash to construct a data set and conducts macro data analysis from a pool level. With the mining pool data publicly as the seed data, we proposed new ideas for exploring mining pool reward transactions from 3 dimensions: active miners, large output transactions, and deshielded value, and found some highly suspicious pool reward distribution addresses. These results can assist in revealing the economic relationship between mining pools and miners at the level of pool participants. In addition, we re-filter the addresses we obtained using cross-comparison to further analysis. Some off-chain public information verifies that our analysis method is effective.
AB - Zcash has attracted the attention of numerous users, including large mining pools, due to its excellent privacy protection and anonymity. The analysis of Zcash mining ecosystem contributes to understanding the evolution trend of cryptocurrency, evaluating system stability, and optimizing network governance. However, limited by the pseudonym mechanism and shielded pool of Zcash, there is little research on Zcash mining. Existing analysis of blockchain mining is limited to Bitcoin and Ethereum, where their methods are useless on Zcash with its enhanced privacy protection. To solve the above problems, this paper uses the block data of Zcash to construct a data set and conducts macro data analysis from a pool level. With the mining pool data publicly as the seed data, we proposed new ideas for exploring mining pool reward transactions from 3 dimensions: active miners, large output transactions, and deshielded value, and found some highly suspicious pool reward distribution addresses. These results can assist in revealing the economic relationship between mining pools and miners at the level of pool participants. In addition, we re-filter the addresses we obtained using cross-comparison to further analysis. Some off-chain public information verifies that our analysis method is effective.
KW - Blockchain
KW - Incentive Mechanism
KW - Mining pool participant
KW - Zcash
UR - http://www.scopus.com/inward/record.url?scp=85184993215&partnerID=8YFLogxK
U2 - 10.1109/CCSB60789.2023.10398799
DO - 10.1109/CCSB60789.2023.10398799
M3 - Conference contribution
AN - SCOPUS:85184993215
T3 - 2023 3rd International Conference on Computer Science and Blockchain, CCSB 2023
SP - 19
EP - 25
BT - 2023 3rd International Conference on Computer Science and Blockchain, CCSB 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Computer Science and Blockchain, CCSB 2023
Y2 - 17 November 2023 through 19 November 2023
ER -