Pinocchio coin: building zerocoin from a succinct pairing-based proof system

By George Danezis, Cédric Fournet, Markulf Kohlweiss, Bryan Parno. 2013

127 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Privacy & Security

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Citations in the corpus

Geppetto: Versatile Verifiable Computation (2015, methodology): “As another example, recent work [7, 25] shows how to anonymize Bitcoin transactions using Pinocchio [46] and would benefit from the ability to verify signatures within transactions.”
Zerocash: Decentralized Anonymous Payments from Bitcoin (2014, methodology): “First, [19]’s protocol, like Zerocoin, only supports fixed-value coins, and is best viewed as a decentralized mix.”
CoinShuffle: Practical Decentralized Coin Mixing for Bitcoin (2014, background): “Zerocoin [16] and its successors [17] [18] [19] provide strong anonymity without any third party, but lack compatibility with the current Bitcoin system.”
Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts (2016, methodology): “Although there has been progress in designing privacy-preserving cryptocurrencies such as Zerocash [11] and several others [26], [43], [54], these systems forgo programmability, and it is unclear a priori how to enable programmability without exposing transactions and data in cleartext to miners.”
Efficient RAM and control flow in verifiable outsourced computation (2015, background): “Buffet allows the programmer to express programs in an expansive subset of C (disallowing only “goto” and function pointers), can handle essentially any example in the verifiable computation literature, and achieves the best performance in the area by multiple orders of magnitude.”
Full Accounting for Verifiable Outsourcing (2017, background): “Before continuing, we note that SNARKs apply more widely, for example to cryptocurrencies [18, 38] and beyond [39, 64].”
Zether: Towards Privacy in a Smart Contract World (2020, background): “Unfortunately, almost all known ways to transfer confidentially [59, 67, 64, 30, 3] are in the unspenttransaction-output (UTXO) model (popularized by Bitcoin), where the inputs to a new transaction are the unspent outputs of previous transactions.”
Verifying computations without reexecuting them (2015, background): “A speculative application is to produce versions of Bitcoin in which transactions can be conducted anonymously, in contrast to the status quo [5, 19].”
Centrally Banked Cryptocurrencies (2015, methodology): “For example, to ensure privacy for transactions, one could adapt existing cryptographic techniques such as those employed by Zerocoin [23], Zerocash [4], Pinocchio Coin [7], or Groth and Kohlweiss [12].”
Mixcoin: Anonymity for Bitcoin with Accountable Mixes (2014, background): “Unfortunately Zerocoin and related proposals [4,9] require modifications to Bitcoin which appear unlikely due to the computational overhead.”
Solidus: Confidential Distributed Ledger Transactions via PVORM (2017, background): “Zcash, a recently deployed decentralized cryptocurrency, and its academic antecedents [7, 25, 46] and offshoots e.”