Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability
Selfish mining is a typical malicious attack targeting the blockchain-based bitcoin system, an emerging crypto asset. Because of the non-incentive compatibility of the bitcoin mining protocol, the attackers are able to collect unfair mining rewards by intentionally withholding blocks. The existing w...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/1/422 |
| _version_ | 1797626290634752000 |
|---|---|
| author | Chencheng Zhou Liudong Xing Qisi Liu Honggang Wang |
| author_facet | Chencheng Zhou Liudong Xing Qisi Liu Honggang Wang |
| author_sort | Chencheng Zhou |
| collection | DOAJ |
| description | Selfish mining is a typical malicious attack targeting the blockchain-based bitcoin system, an emerging crypto asset. Because of the non-incentive compatibility of the bitcoin mining protocol, the attackers are able to collect unfair mining rewards by intentionally withholding blocks. The existing works on selfish mining mostly focused on cryptography design, and malicious behavior detection based on different approaches, such as machine learning or timestamp. Most defense strategies show their effectiveness in the perspective of reward reduced. No work has been performed to design a defense strategy that aims to improve bitcoin dependability and provide a framework for quantitively evaluating the improvement. In this paper, we contribute by proposing two network-wide defensive strategies: the dynamic difficulty adjustment algorithm (DDAA) and the acceptance limitation policy (ALP). The DDAA increases the mining difficulty dynamically once a selfish mining behavior is detected, while the ALP incorporates a limitation to the acceptance rate when multiple blocks are broadcast at the same time. Both strategies are designed to disincentivize dishonest selfish miners and increase the system’s resilience to the selfish mining attack. A continuous-time Markov chain model is used to quantify the improvement in bitcoin dependability made by the proposed defense strategies. Statistical analysis is applied to evaluate the feasibility of the proposed strategies. The proposed DDAA and ALP methods are also compared to an existing timestamp-based defense strategy, revealing that the DDAA is the most effective in improving bitcoin’s dependability. |
| first_indexed | 2024-03-11T10:08:19Z |
| format | Article |
| id | doaj.art-d78b828ce67b40309c8d052ab5f592a5 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:08:19Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d78b828ce67b40309c8d052ab5f592a52023-11-16T14:56:51ZengMDPI AGApplied Sciences2076-34172022-12-0113142210.3390/app13010422Effective Selfish Mining Defense Strategies to Improve Bitcoin DependabilityChencheng Zhou0Liudong Xing1Qisi Liu2Honggang Wang3Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USADepartment of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USADepartment of Electrical and Computer Engineering, University of Hartford, Hartford, CT 06117, USADepartment of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USASelfish mining is a typical malicious attack targeting the blockchain-based bitcoin system, an emerging crypto asset. Because of the non-incentive compatibility of the bitcoin mining protocol, the attackers are able to collect unfair mining rewards by intentionally withholding blocks. The existing works on selfish mining mostly focused on cryptography design, and malicious behavior detection based on different approaches, such as machine learning or timestamp. Most defense strategies show their effectiveness in the perspective of reward reduced. No work has been performed to design a defense strategy that aims to improve bitcoin dependability and provide a framework for quantitively evaluating the improvement. In this paper, we contribute by proposing two network-wide defensive strategies: the dynamic difficulty adjustment algorithm (DDAA) and the acceptance limitation policy (ALP). The DDAA increases the mining difficulty dynamically once a selfish mining behavior is detected, while the ALP incorporates a limitation to the acceptance rate when multiple blocks are broadcast at the same time. Both strategies are designed to disincentivize dishonest selfish miners and increase the system’s resilience to the selfish mining attack. A continuous-time Markov chain model is used to quantify the improvement in bitcoin dependability made by the proposed defense strategies. Statistical analysis is applied to evaluate the feasibility of the proposed strategies. The proposed DDAA and ALP methods are also compared to an existing timestamp-based defense strategy, revealing that the DDAA is the most effective in improving bitcoin’s dependability.https://www.mdpi.com/2076-3417/13/1/422bitcoinselfish miningdynamic difficulty adjustment algorithm (DDAA)acceptance limitation policy (ALP)statistical analysis |
| spellingShingle | Chencheng Zhou Liudong Xing Qisi Liu Honggang Wang Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability Applied Sciences bitcoin selfish mining dynamic difficulty adjustment algorithm (DDAA) acceptance limitation policy (ALP) statistical analysis |
| title | Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability |
| title_full | Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability |
| title_fullStr | Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability |
| title_full_unstemmed | Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability |
| title_short | Effective Selfish Mining Defense Strategies to Improve Bitcoin Dependability |
| title_sort | effective selfish mining defense strategies to improve bitcoin dependability |
| topic | bitcoin selfish mining dynamic difficulty adjustment algorithm (DDAA) acceptance limitation policy (ALP) statistical analysis |
| url | https://www.mdpi.com/2076-3417/13/1/422 |
| work_keys_str_mv | AT chenchengzhou effectiveselfishminingdefensestrategiestoimprovebitcoindependability AT liudongxing effectiveselfishminingdefensestrategiestoimprovebitcoindependability AT qisiliu effectiveselfishminingdefensestrategiestoimprovebitcoindependability AT honggangwang effectiveselfishminingdefensestrategiestoimprovebitcoindependability |