KSG: A Symbolic Semantics Graph Generation Method of Smart Contract Based on the K Framework.

With the help of pact technology, a program that has been developed, the smart contract can take place between two or more entities without any third-party actor. Although smart contracts provide transparency and efficiency, security flaws in smart contracts have resulted in costly attacks, including re-entrancy, integer overflows, and access control violations. Current tools for intelligent contract verification, such as Mythril, Oyente, and Securify, mainly apply symbolic execution, taint analysis, and pattern matching to identify vulnerabilities. However, these tools have many false positives, take a lot of time to execute, and don't scale efficiently with large numbers of contracts. In this context, the paper presents VeriChain. This formal verification framework combines Control Flow Graph (CFG) analysis, symbolic execution, and static analysis to improve vulnerability detection and tackle the challenges above. VeriChain systematically constructs the contract’s Control Flow Graph (CFG), explores CFG execution paths with symbolic execution, and employs a set of rules for performing rule-based static analysis that can uncover vulnerabilities. Using CFG-based dependency tracking, VeriChain achieves enhanced analysis of dependencies among functions and coverage of execution paths, thereby reducing the number of false positives while achieving accurate detection results. The experimental results show that VeriChain obtains 98.3% detection accuracy, higher than Mythril, Oyente, and Securify. Compared to existing tools, VeriChain has a much lower false-positive rate (1 false alarm) and a much faster execution time (Running in only 2.3 seconds). This framework gives a structured security assessment by categorizing the vulnerabilities according to severity and execution traces, ensuring that the smart contracts are accessed under heavy security verification pre-deployment. With its ability to accomplish highly accurate results efficiently whilst providing structured ways to report on security, VeriChain will be an influential component in delivering safe, innovative contract launches to decentralized applications for blockchain developers and security analysts.

Smart contract vulnerability detection based on semantic graph and residual graph convolutional networks with edge attention

Block chain technology provides a decentralized and secure platform for executing transactions. Smart contracts in Ethereum have been proposed as the mechanism to automate legal contracts securely without the involvement of third parties. Yet, there are still several issues to be resolved especially regarding the updating of smart contracts in blockchain as well as the use of blockchain as part of a legal smart contracts system. In this work we propose a methodology and an architecture for building and deploying legal contracts in the blockchain. As the blockchain is immutable, we cannot update the code of the smart legal contracts, but in real life applications updating of contracts is a requirement that cannot be ignored. In this paper we address the problem of contract update by introducing a new versioning system that keeps track of the changes and links the different versions using a linked list. Moreover, we propose a system architecture where the user interface, the application logic and the blockchain are smoothly integrated in a manner that each part of the system contributes for producing a flexible and transparent execution. We show the applicability of our approach by implementing a system for the case of a rental agreement.

Bridging the gap: Predictive contracts in blockchain-achieving recalibration for industrial networks

There are more than 1 million smart contracts in Ethereum and the number of ethers managed by smart contracts has exceeded 100 million, but the security vulnerabilities in smart contracts seriously jeopardize the financial security of Ethereum users. Existing method for defect detection of smart contract bytecode using symbolic execution does not take care of the accuracy and detection realtime at same time. In this paper a smart contract bytecode defect detection algorithm based on parallel symbolic execution is proposed. We split a smart contract in units of functions by analyzing the smart contract function selection process. A symbolic execution tree is constructed for each function to predict the function execution path. Then we partition the symbolic execution tree into multiple sub-trees evenly. Finally, a process pool is used to perform parallel symbolic execution on those sub-trees to reduce the analysis time of smart contract defect detection. Experimental data shows our method has a significant improvement in detection efficiency compared with existing symbolic execution method. The speedup ratio is up to 3.1x in a 4-core computer. Besides, it does not introduce false positives or false negatives.

Smart contracts in blockchain systems are widely used as automated agreements that can expedite the execution of a contract. Based on the characteristics of smart contracts analyzed through agreements in the Indonesian Civil Code (BW), it can be concluded that smart contracts can be legally used in contractual legal activities in Indonesia. This is because smart contracts meet the requirements outlined in the BW as guidelines for contract formation, particularly concerning the validity of contracts. Using a normative method, which employs literature as legal material for this writing, the result shows that the validity of smart contracts in blockchain, based on Indonesian contract law, aligns with the contract law that fulfills the requirements of Article 1320 BW. Smart contracts can also be classified as standard agreements where the parties agree based on an existing and mutually agreed-upon contract. Until now, there are no specific regulations regarding smart contracts in Indonesia, even though smart contracts are already widely used in the country.

Nowadays, blockchain technology and industry has developed rapidly all over the world, which is inseparable from continuous innovation and improvement on smart contract technology. Therefore, by summarizing the working principle and application research status of blockchain smart contract, this paper analyzes the development and challenges of smart contract. Firstly, we introduce the model and operation principle of blockchain smart contract for the overall architecture, analyze the deployment process of smart contract with Ethereum, Hyperledger Fabric and EOSIO, and make a comparative analysis from the technical level. And taking Byteball, InterValue and IOTA platforms as examples, we introduce the deployment process and application potential for DAG-based blockchain smart contract. Additionally, we also summarize the application research of smart contract for international and Blockchain Oracle, and discuss its innovative application and development trend in the future. Secondly, we introduce the application status of smart contract with Ethereum and Hyperledger Fabric platforms from the aspects of financial transactions, Internet of things, medical applications, and supply chain, and further discuss EOS (enterprise operation system), Blockchain Oracle and other application fields. Furthermore, we introduce the application advantages and challenges to smart contract for industrial Internet from the fields of manufacturing, food industry, industrial Internet of things and industry 4.0. Finally, we discuss the challenges faced by smart contract with technical issues, analyzes the impact on large-scale applications and mining system on the sustainable development of smart contract, and looks forward to the future research direction of blockchain smart contract.

Semantic Interoperability on Blockchain by Generating Smart Contracts Based on Knowledge Graphs

Blockchains-based smart contracts are disrupting the smart real estate sector of the smart cities. The current study explores the literature focused on blockchain smart contracts in smart real estate and proposes a conceptual framework for its adoption in smart cities. Based on a systematic review method, the literature published between 2000 and 2020 is explored and analyzed. From the literature, ten key aspects of the blockchain smart contracts are highlighted that are grouped into six layers for adopting the smart contracts in smart real estate. The decentralized application and its interactions with Ethereum Virtual Machine (EVM) are presented to show the development of a smart contract that can be used for blockchain smart contracts in real estate. Further, a detailed design and interaction mechanism are highlighted for the real estate owners and users as parties to a smart contract. A list of functions for initiating, creating, modifying, or terminating a smart contract is presented along with a stepwise procedure for establishing and terminating smart contracts. The current study can help the users enjoy a more immersive, user-friendly, and visualized contracting process, whereas the owners, property technologies (Proptech) companies, and real estate agents can enjoy more business and sales. This can help disrupt traditional real estate and transform it into smart real estate in line with industry 4.0 requirements.

Blockchain is a revolutionary technology that offers a new kind of inventive service. It can handle a variety of sophisticated issues associated with the secrecy, integrity, and availability of fast and secure distributed systems. This concept paper begins by addressing the shift in people's attitudes towards the insurance industry, particularly in Malaysia, and then goes on to understand how the Unified Theory of Acceptance and Use of Technology (UTAUT), Task Technology Fit (TTF), and Initial Trust Model (ITM), influence behavioural intentions in using blockchain smart contracts. A digital insurance platform must be redefined after the increase in online insurance sales transactions prompted by COVID-19 to satisfy the market's expectations. Whereas traditional paper contracts rely on middlemen for execution, blockchain smart contracts are now based on blockchains, which include an immutable record of data and the ability to remove single points of failure. Despite the growing popularity of blockchain research in recent years, research on blockchain smart contract adoption behaviour at the individual level concerning insurance services remains limited. Hence, this study utilises the three models to characterise how performance expectancy, technological context, and initial trust interact to forecast behavioural intention. Furthermore, we stressed the need for additional research to demonstrate the intention to employ blockchain smart contracts is impacted by performance anticipation, technical environment, and personal initial trust. Based on the review, we will design realistic research that will incorporate prospects for theoretical progress as well as empirical discoveries in blockchain smart contract studies. The findings are intended to assist policymakers in developing suitable and improved strategies for capturing interest in blockchain smart contract insurance services in the Malaysian market. We also believe that the evolution of blockchain technology in tandem with smart contracts will enable the creation of new sorts of innovative services, such as insurance.

With the wide application of Internet of Things and blockchain, research on smart contracts has received increased attention, and security threat detection for smart contracts is one of the main focuses. This article first introduces the common security vulnerabilities in blockchain smart contracts, and then classifies the vulnerabilities detection tools for smart contracts into six categories according to the different detection methods: 1) formal verification method; 2) symbol execution method; 3) fuzzy testing method; 4) intermediate representation method; 5) stain analysis method; and 6) deep learning method. We test 27 detection tools and analyze them from several perspectives, including the capability of detecting a smart contract version. Finally, it is concluded that most of the current vulnerability detection tools can only detect vulnerabilities in a single and old version of smart contracts. Although the deep learning method detects fewer types of smart contract vulnerabilities, it has higher detection accuracy and efficiency. Therefore, the combination of static detection methods, such as deep learning method and dynamic detection methods, including the fuzzy testing method to detect more types of vulnerabilities in multi-version smart contracts to achieve higher accuracy is a direction worthy of research in the future.

Blockchain is an emerging technology that underlies creation and exchange of the digital assets, including cryptocurrency such as Bitcoin and Ether, without the need for a central authority. It provides a public ledger for recording sequence of transactions in blocks that are linked as a chain. Smart contracts are computer programs governing participant agreements that are automatically enforced by consensus protocols in the blockchain. Together, blockchain and smart contracts revolutionize efficient transaction stores, services and workflows that work even among distrusting participants and without a trusted authority. Unfortunately, like most software, smart contracts are vulnerable as evidenced by a recent Decentralized Autonomous Organization (DAO) attack that lost cryptocurrency then-valued about $60 million. Correctness of executions alone is not sufficient to guarantee security of smart contracts. This paper addresses how we can apply model checking, a well-established formal verification technique, to help alleviate security issues in smart contract development. Most existing studies have focused on verification of smart contracts on a specific language and specific platform. Smart contracts may have hidden operational side effects that impact software behaviors. Thus, applying model checking to smart contracts is not necessarily straightforward. This paper presents a general technique for building the core functional models applicable for model checking to identify all possible executions that lead to security breaches. It also shows how resulting executions can be systematically analyzed to help identify security issues. The models are language and system independent in that they can represent any smart contract in any language or any platform. We illustrate and evaluate the technique with a widely used example of a smart contract in a financial system along with experimental results using a well-known model checker, NuSMV in various scenarios.

A smart contract is an agreement between two or more parties, which is executed by the computer code. The code does the execution without giving either party the ability to back out, so it ensures the trustless execution. The smart contract is one of the most important features in blockchain applications, which implements trusted transactions without third parties. However, with the rapid development, blockchain smart contracts have also exposed many security problems, and some attacks caused by contract vulnerabilities have led to terrible losses. In order to better deal with such dilemma, making a comprehensive survey about the security verification of blockchain smart contracts from major scientific databases is quite indispensable. Even though the significance of studying security verification of blockchain smart contracts is evident, it is really fresh yet. The major contributions of our survey work come from three aspects. First, after retrieving all-sided research studies, we select 53 most related papers to show the state-of-the art of this topic, where 20 papers focus on dealing with security assurance of blockchain smart contracts, and 33 papers focus on the correctness verification of blockchain smart contracts. Second, we propose a taxonomy toward the topic of security verification of blockchain smart contracts and discuss the pros and cons of each category of related studies. Third, through in-depth analysis of these studies, we come to know that the correctness verification of smart contracts based on the formal method has already become the more significant and more effective method to validate whether a smart contract is credible and accurate. So, we further present representative studies of formal verification of smart contracts in detail to demonstrate that using a formal method to validate blockchain smart contracts must have a promising and meritorious future.

Because of its unique decentralization, encryption, reliability, and tamper‐proof, the block chain system makes smart contracts break through the shackles of the lack of trusted environment, and its application field keeps expanding. We read the source code and official documents of Bitcoin, Ethereum, and Hyperledger to explore the operation principle and implementation mode of smart contract. By analyzing the evolution process of smart contracts in blockchain and the sequence of its function expansion, according to the multirole business process of supply chain, we design a semipublic smart contract chain model based on Ethereum and Hyperledger in order to provide useful inspiration and help for the future research of smart contracts in blockchain applied in supply chain.

One of the building blocks of our legal and economic systems in society is the indispensable reliance on contracts and trust systems to protect individual rights. Recently smart contracts are becoming prominent parts of various blockchain platforms. The goal of smart contracts is to eliminate the third party and centralized trust systems. Due to recent emergence of smart contracts, there is no well-defined framework that researchers can use to evaluate smart contracts under various blockchain platforms and differentiate between them. In this work, a survey on the prominent smart contract landscape specially those based on blockchain have been conducted. Based on the survey, an evaluation framework to assess smart contracts has been proposed. The framework is a set of criteria based on two major aspects; infrastructure related and development related criteria. The evaluation framework was peer-reviewed for reliability and validity. To measure the applicability of the proposed framework, it has been used to empirically evaluate some of the most prominent smart contract platforms. The results of the empirical evaluation have shown that the Ethereum blockchain smart contract exceeds the others in terms of development tools, resources, and community support. EOS blockchain smart contracts have the best execution speeds, and transaction costs. Lastly, Stellar blockchain has predictability and the best transaction builder to use in smart contract development concerning user friendliness. Recommendations for smart contract developers are provided in light of the research.