Zcash Whitepaper - Decentralized Anonymous Payments from Bitcoin

Zcash Whitepaper - Decentralized Anonymous Payments from Bitcoin

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Currency
Zcash
Symbol
ZEC
Founders
Zooko Wilcox
Abstract
Bitcoin is the first digital currency to see widespread adoption. While payments are conducted between pseudonyms, Bitcoin cannot offer strong privacy guarantees: payment trans- actions are recorded in a public decentralized ledger, from which much information can be deduced. Zerocoin tackles some of these privacy issues by unlinking transactions from the payment’s origin. Yet, it still reveals payments’ destinations and amounts, and is limited in functionality.

In this paper, we construct a full-fledged ledger-based digital currency with strong privacy guarantees. Our results leverage recent advances in zero-knowledge Succinct Non-interactive AR- guments of Knowledge (zk-SNARKs).

First, we formulate and construct decentralized anonymous payment schemes (DAP schemes). A DAP scheme enables users to directly pay each other privately: the corresponding transaction hides the payment’s origin, destination, and transferred amount. We provide formal definitions and proofs of the construction’s security.

Second, we build Zerocash, a practical instantiation of our DAP scheme construction. In Zerocash, transactions are less than 1 kB and take under 6 ms to verify — orders of magnitude more efficient than the less-anonymous Zerocoin and competitive with plain Bitcoin.

Introduction
Bitcoin is the first digital currency to achieve widespread adoption. The currency owes its rise in part to the fact that, unlike traditional e-cash schemes, it requires no trusted parties. Instead of appointing a central bank, Bitcoin leverages a distributed ledger known as the block chain to store transactions made between users. Because the block chain is massively replicated by mutually-distrustful peers, the information it contains is public.

While users may employ many identities (or pseudonyms) to enhance their privacy, an increasing body of research shows that anyone can de-anonymize Bitcoin by using information in the block chain, such as the structure of the transaction graph as well as the value and dates of transactions. As a result, Bitcoin fails to offer even a modicum of the privacy provided by traditional payment systems, let alone the robust privacy of anonymous e-cash schemes.

While Bitcoin is not anonymous itself, those with sufficient motivation can obfuscate their transaction history with the help of mixes (also known as laundries or tumblers). A mix allows users to entrust a set of coins to a pool operated by a central party and then, after some interval, retrieve different coins (with the same total value) from the pool. Yet, mixes suffer from three limitations: (i) the delay to reclaim coins must be large to allow enough coins to be mixed in; (ii) the mix can trace coins; and (iii) the mix may steal coins.1 For users with “something to hide,” these risks may be acceptable. But typical legitimate users (1) wish to keep their spending habits private from their peers, (2) are risk-averse and do not wish to expend continual effort in protecting their privacy, and (3) are often not sufficiently aware of their compromised privacy.

To protect their privacy, users thus need an instant, risk-free, and, most importantly, automatic guarantee that data revealing their spending habits and account balances is not publicly accessible by their neighbors, co-workers, and merchants. Anonymous transactions also guarantee that the market value of a coin is independent of its history, thus ensuring legitimate users’ coins remain fungible.

Zerocoin: A Decentralized Mix
Miers et al. proposed Zerocoin, which extends Bitcoin to provide strong anonymity guarantees. Like many e-cash protocols, Zerocoin employs zero-knowledge proofs to prevent transaction graph analyzes. Unlike earlier practical e-cash protocols, however, Zerocoin does not rely on digital signatures to validate coins, nor does it require a central bank to prevent double spending. Instead, Zerocoin authenticates coins by proving, in zero-knowledge, that they belong to a public list of valid coins (which can be maintained on the blockchain). Yet, rather than a full-fledged anonymous currency, Zerocoin is a decentralized mix, where users may periodically “wash” their bitcoins via the Zerocoin protocol. Routine day-to-day transactions must be conducted via Bitcoin, due to reasons that we now review.

The first reason is performance. Redeeming zerocoins requires double-discrete-logarithm proofs of knowledge, which have size that exceeds 45 kB and require 450 ms to verify (at the 128-bit security level). These proofs must be broadcast through the network, verified by every node, and permanently stored in the ledger. The entailed costs are higher, by orders of magnitude, than those in Bitcoin and can seriously tax a Bitcoin network operating at normal scale.

The second reason is functionality. While Zerocoin constitutes a basic e-cash scheme, it lacks critical features required of full-fledged anonymous payments. First, Zerocoin uses coins of fixed denomination: it does not support payments of exact values, nor does it provide a means to make change following a transaction (i.e., divide coins). Second, Zerocoin has no mechanism for one user to pay another one directly in “zerocoins.” And third, while Zerocoin provides anonymity by unlinking a payment transaction from its origin address, it does not hide the amount or other metadata about transactions occurring on the network.

Conclusion
Decentralized currencies should ensure a user’s privacy from his peers when conducting legitimate financial transactions. Zerocash provides such privacy protection, by hiding user identities, transaction amounts, and account balances from public view. This, however, may be criticized for hampering accountability, regulation, and oversight. Yet, Zerocash need not be limited to enforcing the basic monetary invariants of a currency system. The underlying zk-SNARK cryptographic proof machinery is flexible enough to support a wide range of policies. It can, for example, let a user prove that he paid his due taxes on all transactions without revealing those transactions, their amounts, or even the amount of taxes paid. As long as the policy can be specified by efficient nondeterministic computation using NP statements, it can (in principle) be enforced using zk-SNARKs, and added to Zerocash. This can enable privacy-preserving verification and enforcement of a wide range of compliance and regulatory policies that would otherwise be invasive to check directly or might be bypassed by corrupt authorities. This raises research, policy, and engineering questions over what policies are desirable and practically realizable.

Another research question is what new functionality can be realized by augmenting the capabilities already present inBitcoin’s scripting language with zk-SNARKs that allow fast verification of expressive statements.

Acknowledgements
We thank Amazon for their assistance and kind donation of EC2 resources, and Gregory Maxwell for his advice regarding the Bitcoin codebase. We thank Iddo Ben-Tov and the SCIPRLab members - Daniel Genkin, Lior Greenblat, Shaul Kfir,Gil Timnat and Michael Riabzev - for inspiring discussions.

This work was supported by: Amazon.com through an AWS in Education research grant; the Broadcom Foundation and Tel Aviv University Authentication Initiative; the Center forScience of Information (CSoI), an NSF Science and TechnologyCenter, under grant agreement CCF-0939370; the Check Point Institute for Information Security; the U.S. Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL) under contract FA8750-11-2-0211; the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 240258; the Israeli Centers of Research Excellence I-CORE program (center 4/11); the Israeli Ministry of Science and Technology; the Office of Naval Research under contract N00014-11-1-0470; the Simons Foundation, with a Simons Award for Graduate Students in Theoretical Computer Science; and the Skolkovo Foundation under grant agreement 6926059.

The views expressed are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.