| GONG Xunwu (龚循武)* **,HU Bin*,LIU Xiaodong*,ZHAO Xiaofang* ***.[J].高技术通讯(英文),2022,28(3):259~271 |
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| Efficient and fair coin mixing for Bitcoin |
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| DOI：10.3772/j.issn.1006-6748.2022.03.005 |
| 中文关键词: |
| 英文关键词: coin mixing, trusted execution environment (TEE), blockchain, accountable, anonymity |
| 基金项目: |
| Author Name | Affiliation | | GONG Xunwu (龚循武)* ** | (*Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P.R.China)
(**University of Chinese Academy of Sciences, Beijing 100049, P.R.China)
(***Institute of Intelligent Computing Technology, Chinese Academy of Sciences, Suzhou 215000, P.R.China) | | HU Bin* | (*Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P.R.China)
(**University of Chinese Academy of Sciences, Beijing 100049, P.R.China)
(***Institute of Intelligent Computing Technology, Chinese Academy of Sciences, Suzhou 215000, P.R.China) | | LIU Xiaodong* | (*Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P.R.China)
(**University of Chinese Academy of Sciences, Beijing 100049, P.R.China)
(***Institute of Intelligent Computing Technology, Chinese Academy of Sciences, Suzhou 215000, P.R.China) | | ZHAO Xiaofang* *** | (*Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P.R.China)
(**University of Chinese Academy of Sciences, Beijing 100049, P.R.China)
(***Institute of Intelligent Computing Technology, Chinese Academy of Sciences, Suzhou 215000, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| Bitcoin transactions are pseudo-anonymous, which can be exploited to reveal a user’s private information. To eliminate this threat, this paper presents FairMixer, a highly secure and efficient Bitcoin mixing system using the trusted execution environments (TEEs). With the TEE’s confidentiality and integrity guarantees for code and data, FairMixer enables a correct and privacy-preserving mixing process. However, a TEE-based implementation cannot prevent the manipulation of inputs to the mixer, such as mixing request submissions and blockchain feeds. Against this background, FairMixer captures users’ mixing requests via Bitcoin transactions for deterring a malicious service provider from dropping benign participants. To constrain misbehavior during a mixing mission, a misconduct monitoring mechanism and a penalty mechanism are introduced. The proposed scheme is fully compatible with Bitcoin and forces mixes to be accountable. Finally, a prototype of FairMixer is provided using Intel Software Guard Extensions (SGX) and its performance is evaluated in the Bitcoin Testnet. FairMixer mixes 700 inputs in just 8.39s, which outperforms most existing decentralized mixers. |
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