Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart cont...Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart contracts for personal financial gain, which undermines the integrity of the Ethereum blockchain. This paper proposes a computer program called SADA (Static and Dynamic Analyzer), a novel approach to smart contract vulnerability detection using multiple Large Language Model (LLM) agents to analyze and flag suspicious Solidity code for Ethereum smart contracts. SADA not only improves upon existing vulnerability detection methods but also paves the way for more secure smart contract development practices in the rapidly evolving blockchain ecosystem.展开更多
Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attack...Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.展开更多
Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual ri...Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual rights are straightforwardly enforced.Given the common belief that certain personality traits—such as trustworthiness,reliability,loyalty,thriftiness,and stinginess—are more often linked to conservatives(Republicans)than to liberals(Democrats),we investigate whether companies with conservative chief executive officers(CEOs)secure more advantageous loan terms compared to others.Our findings indicate that firms with conservative CEOs are able to negotiate bank loans with lower interest spreads and upfront fees.While we do not observe a direct impact of CEO overconfidence on loan pricing,we reveal that the combined influence of CEO conservatism and overconfidence contributes to our primary findings.Additionally,we discovered that conservative CEOs tend to receive more favorable non-price conditions(fewer covenants)and are less inclined to offer collateral.展开更多
The Book on Contracts of the Civil Code does not recognize"intellectual property contracts"as nominate contracts.Owing to both substantive and structural shortcomings,the Chapter on Technology Contracts fall...The Book on Contracts of the Civil Code does not recognize"intellectual property contracts"as nominate contracts.Owing to both substantive and structural shortcomings,the Chapter on Technology Contracts falls short of providing comprehensive regulation of transactions involving intellectual property,and its Article 876 linking clause has given rise to legal controversies over application by reference and priority of application.There is therefore an urgent need to recognize intellectual property contracts as a nominate category.The rules on such contracts that are dispersed across standalone intellectual property statutes,specialized regulations,adjudicated cases,and judicial interpretations have already produced decodification and should be integrated in the course of enacting the Intellectual Property Code,so as to achieve the recodification of contracts concerning intellectual property.Specifically,the Chapter on Contracts should consist of two parts,General Provisions and Nominate Contracts,to articulate the common features and specific rules of the various contract types while confirming the applicability of the General Provisions in the Book on Contracts.In this way,systemic disorder from mechanically adding nominate contracts to the Civil Code and unnecessary complexity from creating a separate sectoral contract code can both be avoided,and the status of the Book on Contracts as the basic law in the field of contract can be preserved.展开更多
The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,com...The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine(EVM)-based smart contract platforms due to their distributed security environment limitations.Existing off-chain methods often result in a significant reduction in contract execution efficiency,thus a platform software development kit interface implementation method has become a feasible way to reduce overheads,but this method cannot verify operation correctness and may leak sensitive user data.To solve the above problems,we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations,especially matrix operations,which can guarantee operation correctness and user privacy while ensuring computational efficiency.In this scheme,a verifiable interaction process is designed to verify the computation process and results,and a matrix blinding technology is introduced to protect sensitive user data in the calculation process.The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.展开更多
Smart contracts are self-executing programs on blockchains that manage complex business logic with transparency and integrity.However,their immutability after deployment makes programming errors particularly critical,...Smart contracts are self-executing programs on blockchains that manage complex business logic with transparency and integrity.However,their immutability after deployment makes programming errors particularly critical,as such errors can be exploited to compromise blockchain security.Existing vulnerability detection methods often rely on fixed rules or target specific vulnerabilities,limiting their scalability and adaptability to diverse smart contract scenarios.Furthermore,natural language processing approaches for source code analysis frequently fail to capture program flow,which is essential for identifying structural vulnerabilities.To address these limitations,we propose a novel model that integrates textual and structural information for smart contract vulnerability detection.Our approach employs the CodeBERT NLP model for textual analysis,augmented with structural insights derived from control flow graphs created using the abstract syntax tree and opcode of smart contracts.Each graph node is embedded using Sent2Vec,and centrality analysis is applied to highlight critical paths and nodes within the code.The extracted features are normalized and combined into a prompt for a large language model to detect vulnerabilities effectivel.Experimental results demonstrate the superiority of our model,achieving an accuracy of 86.70%,a recall of 84.87%,a precision of 85.24%,and an F1-score of 84.46%.These outcomes surpass existing methods,including CodeBERT alone(accuracy:81.26%,F1-score:79.84%)and CodeBERT combined with abstract syntax tree analysis(accuracy:83.48%,F1-score:79.65%).The findings underscore the effectiveness of incorporating graph structural information alongside text-based analysis,offering improved scalability and performance in detecting diverse vulnerabilities.展开更多
With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, i...With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD (LSTM-Transformer smart Ponzi schemes detection), which is a Ponzi scheme detection method that combines Long Short-Term Memory (LSTM) and Transformer considering the time-series transaction information of smart contracts as well as the global information. Based on the verified smart contract addresses, account features, and code features are extracted to construct a feature dataset, and the SMOTE-Tomek algorithm is used to deal with the imbalanced data classification problem. By comparing our method with the other four typical detection methods in the experiment, the LT-SPSD method shows significant performance improvement in precision, recall, and F1-score. The results of the experiment confirm the efficacy of the model, which has some application value in Ethereum Ponzi scheme smart contract detection.展开更多
The implementation of the new revenue standard has a far-reaching impact on the accounting treatment of insurance enterprises,and the application of contract settlement accounts,as the key to connect business and fina...The implementation of the new revenue standard has a far-reaching impact on the accounting treatment of insurance enterprises,and the application of contract settlement accounts,as the key to connect business and financial accounting,needs to be standardized.This paper analyzes the core requirements of the new revenue standard,combines the special characteristics of insurance contracts with both service and financial attributes,and explains the logic of setting up and accounting methods of secondary accounts,such as insurance service income and investment component apportionment.In view of the practical pain points such as variable consideration apportionment and reclassification of inter-period contracts,the paper proposes strategies for system upgrading and internal control strengthening.The study shows that standardizing the application of accounts can help enterprises implement the requirements of the standard and improve the quality of financial information.展开更多
Attribute-Based Signature(ABS)is a powerful cryptographic primitive that enables fine-grained access control in distributed systems.However,its high computational cost makes it unsuitable for resource-constrained envi...Attribute-Based Signature(ABS)is a powerful cryptographic primitive that enables fine-grained access control in distributed systems.However,its high computational cost makes it unsuitable for resource-constrained environments,and traditional monotonic access structures are inadequate for handling increasingly complex access policies.In this paper,we propose a novel smart contract-assisted ABS(SC-ABS)algorithm that supports nonmonotonic access structures,aiming to reduce client computing overhead while providingmore expressive and flexible access control.The SC-ABS scheme extends the monotonic access structure by introducing the concept of negative attributes,allowing for more complex and dynamic access policies.By utilizing smart contracts,the algorithmsupports distributed trusted assisted computation,and the computation code is transparent and auditable.Importantly,this design allows information about user attributes to be deployed on smart contracts for computation,both reducing the risk of privacy abuse by semi-honest servers and preventing malicious users from attribute concealment to forge signatures.We prove that SC-ABS satisfies unforgeability and anonymity under a random oracle model,and test the scheme’s cost.Comparedwith existing schemes,this scheme has higher efficiency in client signature and authentication.This scheme reduces the computing burden of users,and the design of smart contracts improves the security of aided computing further,solves the problem of attribute concealment,and expresses a more flexible access structure.The solution enables permission control applications in resource-constrained distributed scenarios,such as the Internet of Things(IoT)and distributed version control systems,where data security and flexible access control are critical.展开更多
In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted...In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted to examine the possible processes modulating the storm size.Azimuthally mean potential vorticity(PV)was found to decrease mainly in the middle to upper troposphere between 50-and 80-km radii.The PV budget results indicate that the advection and generation of mean PV associated with asymmetric processes,rather than the symmetric processes,primarily contributed to the decrease in mean PV.These asymmetric processes leading to a negative PV tendency were likely associated with inactive outer rainbands.In contrast,the tangential winds simultaneously expanded radially outward,possibly related to inner-core diabatic heating.The findings here emphasize the importance of outer rainband activity in tropical cyclone size change.展开更多
With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly important.Blockchain and smart contract technologies,with their decentralized nature,provide ...With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly important.Blockchain and smart contract technologies,with their decentralized nature,provide strong security guarantees for IoT.However,at the same time,smart contracts themselves face numerous security challenges,among which reentrancy vulnerabilities are particularly prominent.Existing detection tools for reentrancy vulnerabilities often suffer from high false positive and false negative rates due to their reliance on identifying patterns related to specific transfer functions.To address these limitations,this paper proposes a novel detection method that combines pattern matching with deep learning.Specifically,we carefully identify and define three common patterns of reentrancy vulnerabilities in smart contracts.Then,we extract key vulnerability features based on these patterns.Furthermore,we employ a Graph Attention Neural Network to extract graph embedding features from the contract graph,capturing the complex relationships between different components of the contract.Finally,we use an attention mechanism to fuse these two sets of feature information,enhancing the weights of effective information and suppressing irrelevant information,thereby significantly improving the accuracy and robustness of vulnerability detection.Experimental results demonstrate that our proposed method outperforms existing state-ofthe-art techniques,achieving a 3.88%improvement in accuracy compared to the latest vulnerability detection model AME(Attentive Multi-Encoder Network).This indicates that our method effectively reduces false positives and false negatives,significantly enhancing the security and reliability of smart contracts in the evolving IoT ecosystem.展开更多
This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,inc...This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,including multi-party data intersection calculation,distributed machine learning,etc.It also compares performance differences,conducts formal verification,points out the value and limitations of architecture innovation,and looks forward to future opportunities.展开更多
AIM:To evaluate the efficacy and safety of combining posterior scleral contraction(PSC)with intravitreal perfluoropropane(C_(3)F_(8))injection in high myopia with macular hole retinal detachment(MHRD).METHODS:A total ...AIM:To evaluate the efficacy and safety of combining posterior scleral contraction(PSC)with intravitreal perfluoropropane(C_(3)F_(8))injection in high myopia with macular hole retinal detachment(MHRD).METHODS:A total of 22 participants(22 eyes)with high myopia[axial length(AL)≥26.5 mm]and MHRD who underwent PSC combined with intravitreal C_(3)F_(8)injection,with at least 6mo of follow-up were retrospectively recruited.Outcome measures included best-corrected visual acuity(BCVA),AL,optical coherence tomography(OCT)findings,and adverse events.Retinal recovery was categorized as type Ⅰ(macular hole bridging with retinal reattachment)or type Ⅱ(reattachment without hole bridging).RESULTS:The mean age of participants was 62.1±8.8y and mean follow-up duration was 9.18±4.21mo.Complete retinal reattachment was observed in 11 eyes(50%)at postoperative day 1,19 eyes(86.3%)at week 1,and all 22 eyes at month 1.Ten eyes(45.5%)achieved type Ⅰ recovery and 12 eyes(54.5%)achieved type Ⅱ.Mean BCVA improved from 1.68±0.84 logMAR before surgery to 1.21±0.65 logMAR after surgery(P<0.001),and AL was significantly reduced compared to baseline(29.07±2.05 vs 30.8±2.2 mm;P<0.001).No serious complications were reported.CONCLUSION:PSC combined with intravitreal C_(3)F_(8)injection is a safe and effective treatment for MHRD in highly myopic eyes,especially for retinal detachment limited within the vascular arcade.展开更多
In this study,we explore some of the best proximity point results for generalized proximal contractions in the setting of double-controlled metric-type spaces.A non-trivial example is given to elucidate our analysis,a...In this study,we explore some of the best proximity point results for generalized proximal contractions in the setting of double-controlled metric-type spaces.A non-trivial example is given to elucidate our analysis,and some novel results are derived.The discovered results generalize previously known results in the context of a double controlled metric type space environment.This article’s proximity point results are the first of their kind in the realm of controlled metric spaces.To build on the results achieved in this article,we present an application demonstrating the usability of the given results.展开更多
In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point res...In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.展开更多
In this paper, by virtue of an inequality and sane analysis techniques, we prove sane convergence theorems cm the iterative process for nonlinear mappings of-pseudo contractive type in named linear spaces, which exten...In this paper, by virtue of an inequality and sane analysis techniques, we prove sane convergence theorems cm the iterative process for nonlinear mappings of-pseudo contractive type in named linear spaces, which extend and improve the corresponding results obtained by others recently.展开更多
In order to curb the manufacturer’s product carbon emission levels, the leading retailer usually offers three contracts to the manufacturer, i.e., wholesale-price contract(WC), cost-sharing contract(CC) and revenue-s...In order to curb the manufacturer’s product carbon emission levels, the leading retailer usually offers three contracts to the manufacturer, i.e., wholesale-price contract(WC), cost-sharing contract(CC) and revenue-sharing contract(RC). The results of implementing the three contracts are discussed and compared. The results reveal that as long as the government levies carbon taxations, all the three contracts can effectively stimulate the manufacturer to invest in carbon emission reduction. Among the three contracts, RC can achieve the highest level of carbon emission reduction of products and the maximum profits for both the manufacturer and retailer in a supply chain. However, the RC fails to reach the level of the centralized supply chain(CSC), thus it cannot coordinate the supply chain. The supply chain members’ contract choices are consistent. Both members prefer RC to the other two contracts. In order to effectively reduce the manufacturer’s carbon emission levels, the government should impose the highest carbon taxation level under RC, the medium carbon taxation level under CC, the lowest carbon taxation level under WC, and the same carbon taxation level as RC under the CSC.展开更多
Smart contracts running on public blockchains are permissionless and decentralized,attracting both developers and malicious participants.Ethereum,the world’s largest decentralized application platform on which more t...Smart contracts running on public blockchains are permissionless and decentralized,attracting both developers and malicious participants.Ethereum,the world’s largest decentralized application platform on which more than 40 million smart contracts are running,is frequently challenged by smart contract vulnerabilities.What’s worse,since the homogeneity of a wide range of smart contracts and the increase in inter-contract dependencies,a vulnerability in a certain smart contract could affect a large number of other contracts in Ethereum.However,little is known about how vulnerable contracts affect other on-chain contracts and which contracts can be affected.Thus,we first present the contract dependency graph(CDG)to perform a vulnerability analysis for Ethereum smart contracts,where CDG characterizes inter-contract dependencies formed by DELEGATECALL-type internal transaction in Ethereum.Then,three generic definitions of security violations against CDG are given for finding respective potential victim contracts affected by different types of vulnerable contracts.Further,we construct the CDG with 195,247 smart contracts active in the latest blocks of the Ethereum and verify the above security violations against CDG by detecting three representative known vulnerabilities.Compared to previous large-scale vulnerability analysis,our analysis scheme marks potential victim contracts that can be affected by different types of vulnerable contracts,and identify their possible risks based on the type of security violation actually occurring.The analysis results show that the proportion of potential victim contracts reaches 14.7%,far more than that of corresponding vulnerable contracts(less than 0.02%)in CDG.展开更多
The purpose of this paper is to introduce the concept of Φ_pseudo contractive type mapping and to study the convergence problem of Ishikawa and Mann iterative processes with error for this kind of mappings. The resul...The purpose of this paper is to introduce the concept of Φ_pseudo contractive type mapping and to study the convergence problem of Ishikawa and Mann iterative processes with error for this kind of mappings. The results presented in this paper improve and extend many authors'recent results.展开更多
文摘Smart contracts on the Ethereum blockchain continue to revolutionize decentralized applications (dApps) by allowing for self-executing agreements. However, bad actors have continuously found ways to exploit smart contracts for personal financial gain, which undermines the integrity of the Ethereum blockchain. This paper proposes a computer program called SADA (Static and Dynamic Analyzer), a novel approach to smart contract vulnerability detection using multiple Large Language Model (LLM) agents to analyze and flag suspicious Solidity code for Ethereum smart contracts. SADA not only improves upon existing vulnerability detection methods but also paves the way for more secure smart contract development practices in the rapidly evolving blockchain ecosystem.
基金partially supported by the National Natural Science Foundation (62272248)the Open Project Fund of State Key Laboratory of Computer Architecture,Institute of Computing Technology,Chinese Academy of Sciences (CARCHA202108,CARCH201905)+1 种基金the Natural Science Foundation of Tianjin (20JCZDJC00610)Sponsored by Zhejiang Lab (2021KF0AB04)。
文摘Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.
文摘Banks rely on soft information when assessing loan applications,making it crucial to evaluate the trustworthiness of potential borrowers in order to set loan conditions,even in a legal environment where contractual rights are straightforwardly enforced.Given the common belief that certain personality traits—such as trustworthiness,reliability,loyalty,thriftiness,and stinginess—are more often linked to conservatives(Republicans)than to liberals(Democrats),we investigate whether companies with conservative chief executive officers(CEOs)secure more advantageous loan terms compared to others.Our findings indicate that firms with conservative CEOs are able to negotiate bank loans with lower interest spreads and upfront fees.While we do not observe a direct impact of CEO overconfidence on loan pricing,we reveal that the combined influence of CEO conservatism and overconfidence contributes to our primary findings.Additionally,we discovered that conservative CEOs tend to receive more favorable non-price conditions(fewer covenants)and are less inclined to offer collateral.
基金Fund Project:NationalSocial Science Fund of China(NSSFC)Key Project 18AFX021:Research on Intellectual Property Legislation Issues in the Post-Civil Code Era。
文摘The Book on Contracts of the Civil Code does not recognize"intellectual property contracts"as nominate contracts.Owing to both substantive and structural shortcomings,the Chapter on Technology Contracts falls short of providing comprehensive regulation of transactions involving intellectual property,and its Article 876 linking clause has given rise to legal controversies over application by reference and priority of application.There is therefore an urgent need to recognize intellectual property contracts as a nominate category.The rules on such contracts that are dispersed across standalone intellectual property statutes,specialized regulations,adjudicated cases,and judicial interpretations have already produced decodification and should be integrated in the course of enacting the Intellectual Property Code,so as to achieve the recodification of contracts concerning intellectual property.Specifically,the Chapter on Contracts should consist of two parts,General Provisions and Nominate Contracts,to articulate the common features and specific rules of the various contract types while confirming the applicability of the General Provisions in the Book on Contracts.In this way,systemic disorder from mechanically adding nominate contracts to the Civil Code and unnecessary complexity from creating a separate sectoral contract code can both be avoided,and the status of the Book on Contracts as the basic law in the field of contract can be preserved.
基金supported in part by the National Natural Science Foundation of China under Grant 62272007,U23B2002in part by the Excellent Young Talents Project of the Beijing Municipal University Teacher Team Construction Support Plan under Grant BPHR202203031+1 种基金in part by the Yunnan Key Laboratory of Blockchain Application Technology under Grant 2021105AG070005(YNB202102)in part by the Open Topics of Key Laboratory of Blockchain Technology and Data Security,The Ministry of Industry and Information Technology of the People’s Republic of China under Grant 20243222。
文摘The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses,which involve the calculation of complex functions,such as matrix operations.However,complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine(EVM)-based smart contract platforms due to their distributed security environment limitations.Existing off-chain methods often result in a significant reduction in contract execution efficiency,thus a platform software development kit interface implementation method has become a feasible way to reduce overheads,but this method cannot verify operation correctness and may leak sensitive user data.To solve the above problems,we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations,especially matrix operations,which can guarantee operation correctness and user privacy while ensuring computational efficiency.In this scheme,a verifiable interaction process is designed to verify the computation process and results,and a matrix blinding technology is introduced to protect sensitive user data in the calculation process.The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.
基金supported by the Seoul Business Agency(SBA),funded by the Seoul Metropolitan Government,through the Seoul R&BD Program(FB240022)by the Korea Institute for Advancement of Technology(KIAT),funded by the Korea Government(MOTIE)(RS-2024-00406796)+1 种基金through the HRD Program for Industrial Innovationby the Excellent Researcher Support Project of Kwangwoon University in 2024.
文摘Smart contracts are self-executing programs on blockchains that manage complex business logic with transparency and integrity.However,their immutability after deployment makes programming errors particularly critical,as such errors can be exploited to compromise blockchain security.Existing vulnerability detection methods often rely on fixed rules or target specific vulnerabilities,limiting their scalability and adaptability to diverse smart contract scenarios.Furthermore,natural language processing approaches for source code analysis frequently fail to capture program flow,which is essential for identifying structural vulnerabilities.To address these limitations,we propose a novel model that integrates textual and structural information for smart contract vulnerability detection.Our approach employs the CodeBERT NLP model for textual analysis,augmented with structural insights derived from control flow graphs created using the abstract syntax tree and opcode of smart contracts.Each graph node is embedded using Sent2Vec,and centrality analysis is applied to highlight critical paths and nodes within the code.The extracted features are normalized and combined into a prompt for a large language model to detect vulnerabilities effectivel.Experimental results demonstrate the superiority of our model,achieving an accuracy of 86.70%,a recall of 84.87%,a precision of 85.24%,and an F1-score of 84.46%.These outcomes surpass existing methods,including CodeBERT alone(accuracy:81.26%,F1-score:79.84%)and CodeBERT combined with abstract syntax tree analysis(accuracy:83.48%,F1-score:79.65%).The findings underscore the effectiveness of incorporating graph structural information alongside text-based analysis,offering improved scalability and performance in detecting diverse vulnerabilities.
基金This work was granted by Qin Xin Talents Cultivation Program(No.QXTCP C202115)Beijing Information Science and Technology University+1 种基金the Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Fund(No.GJJ-23)National Social Science Foundation,China(No.21BTQ079).
文摘With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD (LSTM-Transformer smart Ponzi schemes detection), which is a Ponzi scheme detection method that combines Long Short-Term Memory (LSTM) and Transformer considering the time-series transaction information of smart contracts as well as the global information. Based on the verified smart contract addresses, account features, and code features are extracted to construct a feature dataset, and the SMOTE-Tomek algorithm is used to deal with the imbalanced data classification problem. By comparing our method with the other four typical detection methods in the experiment, the LT-SPSD method shows significant performance improvement in precision, recall, and F1-score. The results of the experiment confirm the efficacy of the model, which has some application value in Ethereum Ponzi scheme smart contract detection.
文摘The implementation of the new revenue standard has a far-reaching impact on the accounting treatment of insurance enterprises,and the application of contract settlement accounts,as the key to connect business and financial accounting,needs to be standardized.This paper analyzes the core requirements of the new revenue standard,combines the special characteristics of insurance contracts with both service and financial attributes,and explains the logic of setting up and accounting methods of secondary accounts,such as insurance service income and investment component apportionment.In view of the practical pain points such as variable consideration apportionment and reclassification of inter-period contracts,the paper proposes strategies for system upgrading and internal control strengthening.The study shows that standardizing the application of accounts can help enterprises implement the requirements of the standard and improve the quality of financial information.
基金supported by National Natural Science Foundation of China.
文摘Attribute-Based Signature(ABS)is a powerful cryptographic primitive that enables fine-grained access control in distributed systems.However,its high computational cost makes it unsuitable for resource-constrained environments,and traditional monotonic access structures are inadequate for handling increasingly complex access policies.In this paper,we propose a novel smart contract-assisted ABS(SC-ABS)algorithm that supports nonmonotonic access structures,aiming to reduce client computing overhead while providingmore expressive and flexible access control.The SC-ABS scheme extends the monotonic access structure by introducing the concept of negative attributes,allowing for more complex and dynamic access policies.By utilizing smart contracts,the algorithmsupports distributed trusted assisted computation,and the computation code is transparent and auditable.Importantly,this design allows information about user attributes to be deployed on smart contracts for computation,both reducing the risk of privacy abuse by semi-honest servers and preventing malicious users from attribute concealment to forge signatures.We prove that SC-ABS satisfies unforgeability and anonymity under a random oracle model,and test the scheme’s cost.Comparedwith existing schemes,this scheme has higher efficiency in client signature and authentication.This scheme reduces the computing burden of users,and the design of smart contracts improves the security of aided computing further,solves the problem of attribute concealment,and expresses a more flexible access structure.The solution enables permission control applications in resource-constrained distributed scenarios,such as the Internet of Things(IoT)and distributed version control systems,where data security and flexible access control are critical.
基金jointly supported by the National Natural Science Foundation of China[grant numbers U2342202 and 42175005]the Qing Lan Project[grant number R2023Q06]。
文摘In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted to examine the possible processes modulating the storm size.Azimuthally mean potential vorticity(PV)was found to decrease mainly in the middle to upper troposphere between 50-and 80-km radii.The PV budget results indicate that the advection and generation of mean PV associated with asymmetric processes,rather than the symmetric processes,primarily contributed to the decrease in mean PV.These asymmetric processes leading to a negative PV tendency were likely associated with inactive outer rainbands.In contrast,the tangential winds simultaneously expanded radially outward,possibly related to inner-core diabatic heating.The findings here emphasize the importance of outer rainband activity in tropical cyclone size change.
基金supported by theHigher Education Research Project of Jilin Province:JGJX24C118the National Defense Basic Scientific Research Program of China(No.JCKY2023602C026).
文摘With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly important.Blockchain and smart contract technologies,with their decentralized nature,provide strong security guarantees for IoT.However,at the same time,smart contracts themselves face numerous security challenges,among which reentrancy vulnerabilities are particularly prominent.Existing detection tools for reentrancy vulnerabilities often suffer from high false positive and false negative rates due to their reliance on identifying patterns related to specific transfer functions.To address these limitations,this paper proposes a novel detection method that combines pattern matching with deep learning.Specifically,we carefully identify and define three common patterns of reentrancy vulnerabilities in smart contracts.Then,we extract key vulnerability features based on these patterns.Furthermore,we employ a Graph Attention Neural Network to extract graph embedding features from the contract graph,capturing the complex relationships between different components of the contract.Finally,we use an attention mechanism to fuse these two sets of feature information,enhancing the weights of effective information and suppressing irrelevant information,thereby significantly improving the accuracy and robustness of vulnerability detection.Experimental results demonstrate that our proposed method outperforms existing state-ofthe-art techniques,achieving a 3.88%improvement in accuracy compared to the latest vulnerability detection model AME(Attentive Multi-Encoder Network).This indicates that our method effectively reduces false positives and false negatives,significantly enhancing the security and reliability of smart contracts in the evolving IoT ecosystem.
文摘This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,including multi-party data intersection calculation,distributed machine learning,etc.It also compares performance differences,conducts formal verification,points out the value and limitations of architecture innovation,and looks forward to future opportunities.
文摘AIM:To evaluate the efficacy and safety of combining posterior scleral contraction(PSC)with intravitreal perfluoropropane(C_(3)F_(8))injection in high myopia with macular hole retinal detachment(MHRD).METHODS:A total of 22 participants(22 eyes)with high myopia[axial length(AL)≥26.5 mm]and MHRD who underwent PSC combined with intravitreal C_(3)F_(8)injection,with at least 6mo of follow-up were retrospectively recruited.Outcome measures included best-corrected visual acuity(BCVA),AL,optical coherence tomography(OCT)findings,and adverse events.Retinal recovery was categorized as type Ⅰ(macular hole bridging with retinal reattachment)or type Ⅱ(reattachment without hole bridging).RESULTS:The mean age of participants was 62.1±8.8y and mean follow-up duration was 9.18±4.21mo.Complete retinal reattachment was observed in 11 eyes(50%)at postoperative day 1,19 eyes(86.3%)at week 1,and all 22 eyes at month 1.Ten eyes(45.5%)achieved type Ⅰ recovery and 12 eyes(54.5%)achieved type Ⅱ.Mean BCVA improved from 1.68±0.84 logMAR before surgery to 1.21±0.65 logMAR after surgery(P<0.001),and AL was significantly reduced compared to baseline(29.07±2.05 vs 30.8±2.2 mm;P<0.001).No serious complications were reported.CONCLUSION:PSC combined with intravitreal C_(3)F_(8)injection is a safe and effective treatment for MHRD in highly myopic eyes,especially for retinal detachment limited within the vascular arcade.
文摘In this study,we explore some of the best proximity point results for generalized proximal contractions in the setting of double-controlled metric-type spaces.A non-trivial example is given to elucidate our analysis,and some novel results are derived.The discovered results generalize previously known results in the context of a double controlled metric type space environment.This article’s proximity point results are the first of their kind in the realm of controlled metric spaces.To build on the results achieved in this article,we present an application demonstrating the usability of the given results.
基金funded by National Science,Research and Innovation Fund(NSRF)King Mongkut's University of Technology North Bangkok with Contract No.KMUTNB-FF-68-B-46.
文摘In this manuscript,the notion of a hesitant fuzzy soft fixed point is introduced.Using this notion and the concept of Suzuki-type(μ,ν)-weak contraction for hesitant fuzzy soft set valued-mapping,some fixed point results are established in the framework of metric spaces.Based on the presented work,some examples reflecting decision-making problems related to real life are also solved.The suggested method’s flexibility and efficacy compared to conventional techniques are demonstrated in decision-making situations involving uncertainty,such as choosing the best options in multi-criteria settings.We noted that the presented work combines and generalizes two major concepts,the idea of soft sets and hesitant fuzzy set-valued mapping from the existing literature.
文摘In this paper, by virtue of an inequality and sane analysis techniques, we prove sane convergence theorems cm the iterative process for nonlinear mappings of-pseudo contractive type in named linear spaces, which extend and improve the corresponding results obtained by others recently.
基金The National Natural Science Foundation of China(No.71531004)
文摘In order to curb the manufacturer’s product carbon emission levels, the leading retailer usually offers three contracts to the manufacturer, i.e., wholesale-price contract(WC), cost-sharing contract(CC) and revenue-sharing contract(RC). The results of implementing the three contracts are discussed and compared. The results reveal that as long as the government levies carbon taxations, all the three contracts can effectively stimulate the manufacturer to invest in carbon emission reduction. Among the three contracts, RC can achieve the highest level of carbon emission reduction of products and the maximum profits for both the manufacturer and retailer in a supply chain. However, the RC fails to reach the level of the centralized supply chain(CSC), thus it cannot coordinate the supply chain. The supply chain members’ contract choices are consistent. Both members prefer RC to the other two contracts. In order to effectively reduce the manufacturer’s carbon emission levels, the government should impose the highest carbon taxation level under RC, the medium carbon taxation level under CC, the lowest carbon taxation level under WC, and the same carbon taxation level as RC under the CSC.
基金supported by the Key R and D Programs of Zhejiang Province under Grant No.2022C01018the Natural Science Foundation of Zhejiang Province under Grant No.LQ20F020019.
文摘Smart contracts running on public blockchains are permissionless and decentralized,attracting both developers and malicious participants.Ethereum,the world’s largest decentralized application platform on which more than 40 million smart contracts are running,is frequently challenged by smart contract vulnerabilities.What’s worse,since the homogeneity of a wide range of smart contracts and the increase in inter-contract dependencies,a vulnerability in a certain smart contract could affect a large number of other contracts in Ethereum.However,little is known about how vulnerable contracts affect other on-chain contracts and which contracts can be affected.Thus,we first present the contract dependency graph(CDG)to perform a vulnerability analysis for Ethereum smart contracts,where CDG characterizes inter-contract dependencies formed by DELEGATECALL-type internal transaction in Ethereum.Then,three generic definitions of security violations against CDG are given for finding respective potential victim contracts affected by different types of vulnerable contracts.Further,we construct the CDG with 195,247 smart contracts active in the latest blocks of the Ethereum and verify the above security violations against CDG by detecting three representative known vulnerabilities.Compared to previous large-scale vulnerability analysis,our analysis scheme marks potential victim contracts that can be affected by different types of vulnerable contracts,and identify their possible risks based on the type of security violation actually occurring.The analysis results show that the proportion of potential victim contracts reaches 14.7%,far more than that of corresponding vulnerable contracts(less than 0.02%)in CDG.
文摘The purpose of this paper is to introduce the concept of Φ_pseudo contractive type mapping and to study the convergence problem of Ishikawa and Mann iterative processes with error for this kind of mappings. The results presented in this paper improve and extend many authors'recent results.
