Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network
Abstract In order to improve the revenue of attacking mining pools and miners under block withholding attack, we propose the miner revenue optimization algorithm (MROA) based on Pareto artificial bee colony in blockchain network. MROA establishes the revenue optimization model of each attacking mini...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-07-01
|
Series: | EURASIP Journal on Wireless Communications and Networking |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13638-021-02018-x |
id |
doaj-e43d38ace3ed4987abab18aee9434b10 |
---|---|
record_format |
Article |
spelling |
doaj-e43d38ace3ed4987abab18aee9434b102021-07-11T11:09:07ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992021-07-012021112810.1186/s13638-021-02018-xMiner revenue optimization algorithm based on Pareto artificial bee colony in blockchain networkYourong Chen0Hao Chen1Meng Han2Banteng Liu3Qiuxia Chen4Zhenghua Ma5Zhangquan Wang6College of Information Science and Technology, Zhejiang Shuren UniversitySchool of Computer Science and Artificial Intellgence, Changzhou UniversityBinjiang Institute, Zhejiang UniversityCollege of Information Science and Technology, Zhejiang Shuren UniversityCollege of Information Science and Technology, Zhejiang Shuren UniversitySchool of Computer Science and Artificial Intellgence, Changzhou UniversityCollege of Information Science and Technology, Zhejiang Shuren UniversityAbstract In order to improve the revenue of attacking mining pools and miners under block withholding attack, we propose the miner revenue optimization algorithm (MROA) based on Pareto artificial bee colony in blockchain network. MROA establishes the revenue optimization model of each attacking mining pool and revenue optimization model of entire attacking mining pools under block withholding attack with the mathematical formulas such as attacking mining pool selection, effective computing power, mining cost and revenue. Then, MROA solves the model by using the modified artificial bee colony algorithm based on the Pareto method. Namely, the employed bee operations include evaluation value calculation, selection probability calculation, crossover operation, mutation operation and Pareto dominance method, and can update each food source. The onlooker bee operations include confirmation probability calculation, crowding degree calculation, neighborhood crossover operation, neighborhood mutation operation and Pareto dominance method, and can find the optimal food source in multidimensional space with smaller distribution density. The scout bee operations delete the local optimal food source that cannot produce new food sources to ensure the diversity of solutions. The simulation results show that no matter how the number of attacking mining pools and the number of miners change, MROA can find a reasonable miner work plan for each attacking mining pool, which increases minimum revenue, average revenue and the evaluation value of optimal solution, and reduces the spacing value and variance of revenue solution set. MROA outperforms the state of the arts such as ABC, NSGA2 and MOPSO.https://doi.org/10.1186/s13638-021-02018-xBlock withholding attackBlockchainPowMining cost |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yourong Chen Hao Chen Meng Han Banteng Liu Qiuxia Chen Zhenghua Ma Zhangquan Wang |
spellingShingle |
Yourong Chen Hao Chen Meng Han Banteng Liu Qiuxia Chen Zhenghua Ma Zhangquan Wang Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network EURASIP Journal on Wireless Communications and Networking Block withholding attack Blockchain Pow Mining cost |
author_facet |
Yourong Chen Hao Chen Meng Han Banteng Liu Qiuxia Chen Zhenghua Ma Zhangquan Wang |
author_sort |
Yourong Chen |
title |
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network |
title_short |
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network |
title_full |
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network |
title_fullStr |
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network |
title_full_unstemmed |
Miner revenue optimization algorithm based on Pareto artificial bee colony in blockchain network |
title_sort |
miner revenue optimization algorithm based on pareto artificial bee colony in blockchain network |
publisher |
SpringerOpen |
series |
EURASIP Journal on Wireless Communications and Networking |
issn |
1687-1499 |
publishDate |
2021-07-01 |
description |
Abstract In order to improve the revenue of attacking mining pools and miners under block withholding attack, we propose the miner revenue optimization algorithm (MROA) based on Pareto artificial bee colony in blockchain network. MROA establishes the revenue optimization model of each attacking mining pool and revenue optimization model of entire attacking mining pools under block withholding attack with the mathematical formulas such as attacking mining pool selection, effective computing power, mining cost and revenue. Then, MROA solves the model by using the modified artificial bee colony algorithm based on the Pareto method. Namely, the employed bee operations include evaluation value calculation, selection probability calculation, crossover operation, mutation operation and Pareto dominance method, and can update each food source. The onlooker bee operations include confirmation probability calculation, crowding degree calculation, neighborhood crossover operation, neighborhood mutation operation and Pareto dominance method, and can find the optimal food source in multidimensional space with smaller distribution density. The scout bee operations delete the local optimal food source that cannot produce new food sources to ensure the diversity of solutions. The simulation results show that no matter how the number of attacking mining pools and the number of miners change, MROA can find a reasonable miner work plan for each attacking mining pool, which increases minimum revenue, average revenue and the evaluation value of optimal solution, and reduces the spacing value and variance of revenue solution set. MROA outperforms the state of the arts such as ABC, NSGA2 and MOPSO. |
topic |
Block withholding attack Blockchain Pow Mining cost |
url |
https://doi.org/10.1186/s13638-021-02018-x |
work_keys_str_mv |
AT yourongchen minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT haochen minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT menghan minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT bantengliu minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT qiuxiachen minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT zhenghuama minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork AT zhangquanwang minerrevenueoptimizationalgorithmbasedonparetoartificialbeecolonyinblockchainnetwork |
_version_ |
1724163249572675584 |