eprintid: 10184999 rev_number: 10 eprint_status: archive userid: 699 dir: disk0/10/18/49/99 datestamp: 2024-01-08 11:07:32 lastmod: 2024-01-08 11:07:32 status_changed: 2024-01-08 11:07:32 type: proceedings_section metadata_visibility: show sword_depositor: 699 creators_name: Wang, Zhipeng creators_name: Chaliasos, Stefanos creators_name: Qin, Kaihua creators_name: Zhou, Liyi creators_name: Gao, Lifeng creators_name: Berrang, Pascal creators_name: Livshits, Benjamin creators_name: Gervais, Arthur title: On How Zero-Knowledge Proof Blockchain Mixers Improve, and Worsen User Privacy ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: Blockchain; Privacy; Anonymity; Mixer; DeFi note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Zero-knowledge proof (ZKP) mixers are one of the most widely-used blockchain privacy solutions, operating on top of smart contract-enabled blockchains. We find that ZKP mixers are tightly intertwined with the growing number of Decentralized Finance (DeFi) attacks and Blockchain Extractable Value (BEV) extractions. Through coin flow tracing, we discover that 205 blockchain attackers and 2, 595 BEV extractors leverage mixers as their source of funds, while depositing a total attack revenue of 412.87M USD. Moreover, the US OFAC sanctions against the largest ZKP mixer, Tornado.Cash, have reduced the mixer’s daily deposits by more than . Further, ZKP mixers advertise their level of privacy through a so-called anonymity set size, which similarly to k-anonymity allows a user to hide among a set of k other users. Through empirical measurements, we, however, find that these anonymity set claims are mostly inaccurate. For the most popular mixers on Ethereum (ETH) and Binance Smart Chain (BSC), we show how to reduce the anonymity set size on average by and respectively. Our empirical evidence is also the first to suggest a differing privacy-predilection of users on ETH and BSC. State-of-the-art ZKP mixers are moreover interwoven with the DeFi ecosystem by offering anonymity mining (AM) incentives, i.e., users receive monetary rewards for mixing coins. However, contrary to the claims of related work, we find that AM does not necessarily improve the quality of a mixer’s anonymity set. Our findings indicate that AM attracts privacy-ignorant users, who then do not contribute to improving the privacy of other mixer users. date: 2023-04-30 date_type: published publisher: ACM (Association for Computing Machinery) official_url: http://dx.doi.org/10.1145/3543507.3583217 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2027786 doi: 10.1145/3543507.3583217 isbn_13: 9781450394161 lyricists_name: Gervais, Arthur lyricists_id: AGERV21 actors_name: Gervais, Arthur actors_id: AGERV21 actors_role: owner full_text_status: public pres_type: paper series: The ACM Web Conference 2023 publication: ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023 volume: 2023 place_of_pub: New York, NY, USA pagerange: 2022-2032 event_title: WWW '23: The ACM Web Conference 2023 book_title: WWW '23: Proceedings of the ACM Web Conference 2023 editors_name: Ding, Ying editors_name: Tang, Jie editors_name: Sequeda, Juan editors_name: Aroyo, Lora editors_name: Castillo, Carlos editors_name: Houben, Geert-Jan citation: Wang, Zhipeng; Chaliasos, Stefanos; Qin, Kaihua; Zhou, Liyi; Gao, Lifeng; Berrang, Pascal; Livshits, Benjamin; Wang, Zhipeng; Chaliasos, Stefanos; Qin, Kaihua; Zhou, Liyi; Gao, Lifeng; Berrang, Pascal; Livshits, Benjamin; Gervais, Arthur; - view fewer <#> (2023) On How Zero-Knowledge Proof Blockchain Mixers Improve, and Worsen User Privacy. In: Ding, Ying and Tang, Jie and Sequeda, Juan and Aroyo, Lora and Castillo, Carlos and Houben, Geert-Jan, (eds.) WWW '23: Proceedings of the ACM Web Conference 2023. (pp. pp. 2022-2032). ACM (Association for Computing Machinery): New York, NY, USA. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10184999/1/2201.09035%20%281%29.pdf