Zero-Collateral Lotteries in Bitcoin and Ethereum

Miller, Andrew; Bentov, Iddo

doi:10.1109/eurospw.2017.44

Cited by 46 publications

(37 citation statements)

References 28 publications

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“…To evaluate our toolchain, we use a benchmark of representative use cases, including financial contracts [17,38], auctions, lotteries [7,33] and gambling games 5 . For each contract in the benchmark, we display in Table 1 the number N of involved participants, the number T of transactions obtained by the compiler, and the verification time V for checking liquidity 6 .…”

Section: Discussionmentioning

confidence: 99%

Developing secure bitcoin contracts with BitML

Atzei

Bartoletti

Lande

et al. 2019

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

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We present a toolchain for developing and verifying smart contracts that can be executed on Bitcoin. The toolchain is based on BitML, a recent domain-specific language for smart contracts with a computationally sound embedding into Bitcoin. Our toolchain automatically verifies relevant properties of contracts, among which liquidity, ensuring that funds do not remain frozen within a contract forever. A compiler is provided to translate BitML contracts into sets of standard Bitcoin transactions: executing a contract corresponds to appending these transactions to the blockchain. We assess our toolchain through a benchmark of representative contracts.Demo Video URL: https://youtu.be/bxx3bM5Pm6c CCS CONCEPTS• Software and its engineering → Software verification; • Security and privacy → Distributed systems security.

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Section: Discussionmentioning

confidence: 99%

Developing secure bitcoin contracts with BitML

Atzei

Bartoletti

Lande

et al. 2019

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

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“…Smart contracts in Bitcoin have a completely different flavour compared to Ethereum, since they are usually expressed as cryptographic protocols, rather than as programs. Despite the limited expressiveness of the scripts in Bitcoin transactions [10], several kinds of contracts for Bitcoin have been proposed [9]: they range from lotteries [6,7,13,29], to general multiparty computations [4,17,26], to contingent payments [11,28], etc. All these works focus on proving the security of a fixed contract, unlike the above-mentioned works on Ethereum, where the goal is to verify arbitrary contracts.…”

Section: Contributionsmentioning

confidence: 99%

Verifying Liquidity of Bitcoin Contracts

Bartoletti

Zunino

2019

Lecture Notes in Computer Science

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A landmark security property of smart contracts is liquidity: in a non-liquid contract, it may happen that some funds remain frozen. The relevance of this issue is witnessed by a recent liquidity attack to the Ethereum Parity Wallet, which has frozen ∼160M USD within the contract, making this sum unredeemable by any user. We address the problem of verifying liquidity of Bitcoin contracts. Focussing on BitML, a contracts DSL with a computationally sound compiler to Bitcoin, we study various notions of liquidity. Our main result is that liquidity of BitML contracts is decidable, in all the proposed variants. To prove this, we first transform the infinite-state semantics of BitML into a finitestate one, which focusses on the behaviour of any given set of contracts, abstracting the context moves. With respect to the chosen contracts, this abstraction is sound and complete. Our decision procedure for liquidity is then based on model-checking the finite space of states of the abstraction.1. We formalize a notion of liquidity (Definition 2), and we illustrate several meaningful variants. Our notion of liquidity takes into account both the contract and the strategy that a participant follows to perform contract actions. Roughly, a strategy is liquid when following it ensures that funds do not remain frozen within the contract, even in the presence of adversaries. 2. We introduce an abstraction of the semantics of BitML which is finite-state (Theorem 1), and sound and complete w.r.t. the concrete (infinite-state) semantics, given a set of contracts under observation (Theorems 2 and 3). 3. We devise a verification technique for liquidity in BitML. Our technique can establish whether a strategy is liquid for a given contract, and also to synthesise a liquid strategy, when it exists (Theorem 4).Our finite-state abstraction is general-purpose: verifying liquidity is only one of its possible applications (some other applications are discussed in Sect. 6). Related Works.Several recent works study security issues related to Ethereum smart contracts. A few papers address EVM, the bytecode language which is the target of compilation of Solidity. Among them, [27] introduces an operational semantics of a simplified version of EVM, and develops Oyente, a tool to detect some vulnerability patterns of EVM contracts through symbolic execution. Securify [35] checks vulnerability patterns by analysing dependency graphs extracted

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“…In addition, BTC is used as a part of fair electronic voting protocol, guaranteeing the security and privacy of voters simultaneously [22]. Moreover, a lottery protocol based on cryptocurrency is proposed [23]. Thanks to the privacy of BTC, the automatic execution of BTC scripts, and the characteristics of P2P networks, BTC is employed in various protocols.…”

Section: Related Workmentioning

confidence: 99%

FaDe: A Blockchain-Based Fair Data Exchange Scheme for Big Data Sharing

Chen

Guo

et al. 2019

Future Internet

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In the big data era, data are envisioned as critical resources with various values, e.g., business intelligence, management efficiency, and financial evaluations. Data sharing is always mandatory for value exchanges and profit promotion. Currently, certain big data markets have been created for facilitating data dissemination and coordinating data transaction, but we have to assume that such centralized management of data sharing must be trustworthy for data privacy and sharing fairness, which very likely imposes limitations such as joining admission, sharing efficiency, and extra costly commissions. To avoid these weaknesses, in this paper, we propose a blockchain-based fair data exchange scheme, called FaDe. FaDe can enable de-centralized data sharing in an autonomous manner, especially guaranteeing trade fairness, sharing efficiency, data privacy, and exchanging automation. A fairness protocol based on bit commitment is proposed. An algorithm based on blockchain script architecture for a smart contract, e.g., by a bitcoin virtual machine, is also proposed and implemented. Extensive analysis justifies that the proposed scheme can guarantee data exchanging without a trusted third party fairly, efficiently, and automatically.

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Zero-Collateral Lotteries in Bitcoin and Ethereum

Cited by 46 publications

References 28 publications

Developing secure bitcoin contracts with BitML

Developing secure bitcoin contracts with BitML

Verifying Liquidity of Bitcoin Contracts

FaDe: A Blockchain-Based Fair Data Exchange Scheme for Big Data Sharing

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