Efficient and fair coin mixing for Bitcoin

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 8.39 s,which outperforms most existing decentralized mixers.