Formal Methods for the Verification of Smart Contracts: A Review

Krichen, Moez; Lahami, Mariam; Al‐Haija, Qasem Abu

doi:10.1109/sin56466.2022.9970534

Cited by 75 publications

(64 citation statements)

References 27 publications

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“…To guarantee the correctness of smart contracts, formal verification of smart contracts is necessary. There are different methods and goals of formal verification, including model checking, theorem proving, symbolic execution, runtime verification, and so on [28]. Reference [29] also provides a list of tools for smart contract verification.…”

Section: Distributed Requester/collaborator Reputationmentioning

confidence: 99%

A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences

Wang

Ai²,

Cao

et al. 2023

Symmetry

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The architecture of cloud–edge collaboration can improve the efficiency of Internet of Things (IoT) systems. Recent studies have pointed out that using IoT terminal devices as destinations for computing offloading can promote further optimized allocation of computational resources. However, in practice, this idea encounters the problem that participants might lack the motivation to take over computational tasks from others. Although the edge and the terminal are provided with symmetrical positions in collaborative offloading, their computational resources and capabilities are asymmetric. To mitigate this issue, this paper designs a distributed strategy for the trading of computational resources. The most prominent feature of our strategy is its multi-preference optimization objective that takes into account the overall satisfaction with task delay, energy cost, trading prices, and user reputation of participants. In addition, this paper proposes a system architecture based on the Blockchain-as-a-Service (BaaS) design to give full play to the good distributed technology features of blockchain, such as decentralization, traceability, immutability, and automation. Meanwhile, BaaS delivers decentralized identifier (DID) based distributed identity infrastructure for the distributed computational resource trading stakeholders as well. In the simulation evaluation, we compare our trading strategy based on a matching mechanism called multi-preference matching (MPM) to trading using the classical double auction (DA) matching mechanism. The results show that our computational resource trading strategy is able to offload and execut more tasks, achieving a better throughput compared to the DA-based strategy.

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Section: Distributed Requester/collaborator Reputationmentioning

confidence: 99%

A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences

Wang

Ai²,

Cao

et al. 2023

Symmetry

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“…Formal verification of the smart contract. Since our scheme applies the smart contract to achieve interaction between blockchain and other entities, we use a formal verification method [33] to verify the correctness of the smart contract to prevent errors and security breaches. Following the idea proposed in [34], we use the BIP (Behavior Interaction Priorities) framework for smart contract verification [35].…”

Section: Security Analysismentioning

confidence: 99%

Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains

Fu,

Zhang,

et al. 2023

Entropy

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Machine learning has become increasingly popular in academic and industrial communities and has been widely implemented in various online applications due to its powerful ability to analyze and use data. Among all the machine learning models, decision tree models stand out due to their great interpretability and simplicity, and have been implemented in cloud computing services for various purposes. Despite its great success, the integrity issue of online decision tree prediction is a growing concern. The correctness and consistency of decision tree predictions in cloud computing systems need more security guarantees since verifying the correctness of the model prediction remains challenging. Meanwhile, blockchain has a promising prospect in two-party machine learning services as the immutable and traceable characteristics satisfy the verifiable settings in machine learning services. In this paper, we initiate the study of decision tree prediction services on blockchain systems and propose VDT, a Verifiable Decision Tree prediction scheme for decision tree prediction. Specifically, by leveraging the Merkle tree and hash function, the scheme allows the service provider to generate a verification proof to convince the client that the output of the decision tree prediction is correctly computed on a particular data sample. It is further extended to an update method for a verifiable decision tree to modify the decision tree model efficiently. We prove the security of the proposed VDT schemes and evaluate their performance using real datasets. Experimental evaluations show that our scheme requires less than one second to produce verifiable proof.

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“…In smart contract-based business process execution, the verification of smart contracts is indispensable and mandatory for achieving trust and security. Program-level and contract-level verifications can bring confidence and reliability to the design and testing of the system [141].…”

Section: Analysis Of the Challengesmentioning

confidence: 99%

Toward Building Smart Contract-Based Higher Education Systems Using Zero-Knowledge Ethereum Virtual Machine

Fekete

Kiss

2023

Electronics

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The issuing and verification of higher education certificates, including all higher education documents, still functions in a costly and inappropriately bureaucratic manner. Blockchain technology provides a more secure and consistent way to revolutionize the widely used generalized mechanisms and system concepts. In this paper, the most necessary requirements are examined regarding a blockchain-based higher education system, based on the most well-known research papers. Moreover, the opportunities of working on an education system by maintaining a decentralized structure organization are recommended as well. This paper recommends the most suitable blockchain scaling solution for the architecture of an education system which uses the most state-of-the-art EVM (Ethereum virtual machine) compatible approach to implement the higher education system with all the predefined requirements. It is proven that the explained smart contract-based higher education system, which uses zkEVM (zero-knowledge Ethereum virtual machine), consists of all necessary functionalities and satisfies all predefined requirements. In fact, the recommended system, by using a modular blockchain structure, implements all the functionality and capability of the examined related works in one system, namely GDPR (General Data Protection Regulation), which is compatible and more secure.

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Formal Methods for the Verification of Smart Contracts: A Review

Cited by 75 publications

References 27 publications

A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences

A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences

Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains

Toward Building Smart Contract-Based Higher Education Systems Using Zero-Knowledge Ethereum Virtual Machine

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