A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

In recent years,the number of smart contracts deployed on blockchain has exploded.However,the issue of vulnerability has caused incalculable losses.Due to the irreversible and immutability of smart contracts,vulnerability detection has become particularly important.With the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts.This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts.Subsequently,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection.These tools are categorized based on their open-source status,the data format and the type of feature extraction they employ.Then we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and accuracy.Finally,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection tools.Meanwhile,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency.Revolutionary advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer environment.ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users.However,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological variation.This may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS services.In this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between vehicles.Self-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed protocol.The results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement

With the increasing popularity of Ethereum,smart contracts have become a prime target for fraudulent activities such as Ponzi,honeypot,gambling,and phishing schemes.While some researchers have studied intelligent fraud detection,most research has focused on identifying Ponzi contracts,with little attention given to detecting and preventing gambling or phishing contracts.There are three main issues with current research.Firstly,there exists a severe data imbalance between fraudulent and non-fraudulent contracts.Secondly,the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent contracts.Lastly,most prior studies have used contract source code as raw features,but many smart contracts only exist in bytecode.To address these issues,we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet(ECA-EfficientNet)and data enhancement.Our method begins by converting bytecode into Red Green Blue(RGB)three-channel images and then applying channel exchange data enhancement.We then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB images.Our proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi,honeypot,gambling,and phishing smart contracts.The results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract detection.Our research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts.

Deep Learning-Based Program-Wide Binary Code Similarity for Smart Contracts

Recently,security issues of smart contracts are arising great attention due to the enormous financial loss caused by vulnerability attacks.There is an increasing need to detect similar codes for hunting vulnerability with the increase of critical security issues in smart contracts.Binary similarity detection that quantitatively measures the given code diffing has been widely adopted to facilitate critical security analysis.However,due to the difference between common programs and smart contract,such as diversity of bytecode generation and highly code homogeneity,directly adopting existing graph matching and machine learning based techniques to smart contracts suffers from low accuracy,poor scalability and the limitation of binary similarity on function level.Therefore,this paper investigates graph neural network to detect smart contract binary code similarity at the program level,where we conduct instruction-level normalization to reduce the noise code for smart contract pre-processing and construct contract control flow graphs to represent smart contracts.In particular,two improved Graph Convolutional Network(GCN)and Message Passing Neural Network(MPNN)models are explored to encode the contract graphs into quantitatively vectors,which can capture the semantic information and the program-wide control flow information with temporal orders.Then we can efficiently accomplish the similarity detection by measuring the distance between two targeted contract embeddings.To evaluate the effectiveness and efficient of our proposed method,extensive experiments are performed on two real-world datasets,i.e.,smart contracts from Ethereum and Enterprise Operation System(EOS)blockchain-based platforms.The results show that our proposed approach outperforms three state-of-the-art methods by a large margin,achieving a great improvement up to 6.1%and 17.06%in accuracy.

Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0

The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

The Characteristics of the Prepositions and Prepositional Phrases in Business English Contracts and Translation

A majority of contracts will use many prepositions and prepositional phrases to reflect their preciseness which cause the treaty wording complicated and hard to understand. This paper tends to demonstrate the characteristics of the prepositions and prepositional phrases used in business English contracts and explore the translation strategies used in translating the features of the prepositions and the prepositional phrases in business English contracts. The findings of this paper can provide a reference for the majority of the trade workers, which can help them accurately and effectively draft or translate a contract and avoid unnecessary disputes.

Modeling China's offshore production sharing contracts using meta analysis

Production sharing contracts have been used in the development of China’s offshore petroleum resources since 1982, but the mechanism in which the fiscal terms impact project economics is complicated and not well understood. The purpose of this paper is to model China’s offshore production sharing contracts using a probabilistic approach. Cash flows and economic indicators are used for a typical offshore oilfield development, and meta-models are constructed to analyze the basic features of the fiscal system. Applications of the models in contract negotiation are discussed.

Supply chain coordination mechanisms under flexible contracts

In supply chain management,an important research direction is to coordinate the supply chain through introducing flexible contracts.A supply chain contract is flexible if it can satisfy two conditions at the same time：the supply chain is coordinated,and the total profit of the supply chain can be arbitrarily divided between the supply chain members.This paper puts out two contracts,a flexible return contract and a flexible wholesale price discount contract.In contrast to many of literature,the supply chain contracts with an endogenous wholesale price is specifically considered,and a detailed sensitivity analysis of the contract parameters is given.The paper also discusses the application of the contract in vendor-managed inventory（VMI） mode.The results show that the supply chain＇s performance is improved after introducing above contracts.All the findings are illustrated by numerical examples.

Mining Bytecode Features of Smart Contracts to Detect PonziScheme on Blockchain

The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in untrustworthy environments.However,these features of this technology are also easily exploited by unscrupulous individuals,a typical example of which is the Ponzi scheme in Ethereum.The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant.To solve this problem,we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode.In this model,our innovation is shown in two aspects:We first propose to use two bytes as one characteristic,which can quickly transform the bytecode into a high-dimensional matrix,and this matrix contains all the implied characteristics in the bytecode.Then,We innovatively transformed the Ponzi schemes detection into an anomaly detection problem.Finally,an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts.Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts.Moreover,the F1-score of this model can reach 0.88,which is far better than those of other traditional detection models.

Elastic Smart Contracts in Blockchains

In this paper,we deal with questions related to blockchains in complex Internet of Things(IoT)-based ecosystems.Such ecosystems are typically composed of IoT devices,edge devices,cloud computing software services,as well as people,who are decision makers in scenarios such as smart cities.Many decisions related to analytics can be based on data coming from IoT sensors,software services,and people.However,they are typically based on different levels of abstraction and granularity.This poses a number of challenges when multiple blockchains are used together with smart contracts.This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT.We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario,discussing the benefits in terms of performance and self-adaptability of our solution.

Modeling optimal oil production paths under risk service contracts

Due to the rigorous fiscal terms and huge potential risk of risk service contracts,optimizing oil production paths is one of the main challenges in designing oilfield development plans.In this paper,an oil production path optimization model is developed to maximize economic benefits within constraints of technology factors and oil contracts.This analysis describes the effects of risk service contract terms on parameters of inputs and outputs and quantifies the relationships between production and production time,revenues,investment and costs.An oil service development and production project is illustrated in which the optimal production path under its own geological conditions and contract terms is calculated.The influences of oil price,service fees per barrel and operating costs on the optimal production have been examined by sensitivity analysis.The results show that the oil price has the largest impact on the optimal production,which is negatively related to oil price and positively related to service fees per barrel and operating costs.

Pareto Optimal Solution for Supply Contracts with Multiple Suppliers

This paper analyzes an electronic procurement （e-procurement） process between a manufacturer and N-supplier in the e-market. We proof that using the general contract based on auction theory, i. e. the wholesale price contract, would not achieve the coordination of channel composed of the manufacturer and the winning supplier. The paper designs a contract mechanism, i.e. the side payment price-restricted contract based on auction theory, which not only ensures Pareto optimal solutions for both, but also coordinates the supply chain. A numerical experiment is provided to compare the performance of different auction mechanisms and to reinforce key managerial insights generated through analysis.

A Review of Deepwater Pipeline Construction in the U.S. Gulf of Mexico-Contracts, Cost, and Installation Methods

The offshore pipeline network in the U.S. Gulf of Mexico is the largest and most transparent system in the world. A review of deepwater projects in the region provides insight into construction cost and installation methods and the evolution of contract strategies. Pipeline projects are identified as export systems, infield flowline systems, and combined export and infield systems, and three dozen deepwater pipeline installations from 1980–2014 are described based on Offshore Technology Conference(OTC) and Society of Petroleum Engineers(SPE) industry publications and press release data. Export lines and infield flowlines are equally represented and many projects used a combination of J-lay, S-lay and reel methods with rigid steel, flexible line, and pipe-in-pipe systems. The average 2014 inflation-adjusted cost for pipeline projects based on OTC/SPE publications was $2.76 million/mi and ranged from $520 000/mi to $12.94 million/mi. High cost pipelines tend to be short segments or specialized pipeline. Excluding the two cost endpoints, the majority of projects ranged from $1 to $6 million/mi. The average inflation-adjusted cost to install deepwater pipelines in the U.S. Gulf of Mexico based on available public data is estimated at $3.1 million/mi.

Incentive Contracts for Venture Capital Syndication

Aiming at the incentive problems of venture capital syndication at the second and later stages, an game model is set up by principal agent and incentive theory, given that the lead venture capitalist has already some knowledge of the project quality from his initial funding of the project. Under symmetric and asymmetric information, the model analyzes how the optimal syndication contracts induce venture capitalists to truthfully reveal their information to each other, and vary with the level of venture capitalists＇ expertise and information in evaluating projects.

Barriers to the Adoption of BOT Contracts System for Infrastructural Development of Technical Universities in Ghana

The study was conducted with the aim of exploring the barriers to the adoption of BOT contract systems for infrastructural development of technical universities in Ghana. In an empirical questionnaire survey with professionals and experts in the construction and education sector, the respondents were invited to rate their perception on the barriers to the adoption of the BOT contracts systems. An interview session to satisfy ways of adopting the BOT contracts for infrastructural development in technical universities was conducted with selected professionals. The study revealed that the major barriers to the adoption of the BOT contract system are: delays in approval, corruption, reliability and credit worthiness of entities and expropriation. The study suggested that detailed policy or framework for implementing BOT contracts;proper planning by technical universities;and adequate protection for lenders is required for successful BOT implementation. Therefore there is a need to explore this concept, using adequate policy initiatives, proper measures and support from government to improve on the proper implementation of the BOT contracts in Technical Universities in Ghana.

Exploring the Main Factors Affecting Consumer Choice of Mobile Phone Service Provider Contracts

This study aims to investigate the main factors affecting a consumer’s choice of mobile phone service provider contracts, and to determine which of these factors are important in a consumer’s decision-making process. As this decision is particularly pertinent within the contractual behavior setting, there is a need to explore the main factors that shape mobile phone subscriber choices when entering into a mobile phone telecommunication service contract. To do so, a set of mobile interrelated contract dimensions and a set of mobile service provider interrelated dimensions were identified and tested. The convenience sampling technique was employed and 400 questionnaires were distributed to mobile phone subscribers in Jordan with a response rate of 78.5%. By using the regression analysis, result analysis revealed that the main factor affecting consumer choices was “contract features”, with a relative importance of 41%. After a set of mobile phone contract hypotheses were identified and tested, it was found that contract price, with about 15% relative importance, was the main contract feature that affected consumer choices, followed by the size of data that were related to the number of minutes and/or number of messages offered within the mobile service contract package. In addition, “company factors”, with about 18% relative importance, were found to affect consumer choice of service provider contracts. The principal issue affecting consumer choice decisions was “switching cost”, which was the highest relative importance element of company interrelated factors and found to influence mobile subscriber contracts choice significantly. However, other company factors like signal strength and sales outlet availability had no significant impact on consumer choices and ranked less for consumer-choice priority. More attention is needed from scholars to study the effect of other possible mobile phone contract dimensions from customers’ perspective.

Electronic Auction Scheme Based on Smart Contract and IPFS

Sealed-bid auctions are a vital transaction tool in the e-commerce field.Traditional centralized auction schemes typically result in severe threats to data integrity,information transparency,and traceability owing to their excessive reliance on third parties,and blockchain-based auction schemes generally suffer from high storage costs and are deficient in functional and architectural design.To solve these problems,this study presents a sealed-bid auction scheme that removes the third-party based on an Ethereum smart contract,ensuring data integrity,openness,and transparency in the execution process.The commitment mechanism and distributed storage system help to significantly reduce the user’s storage cost and protect the privacy of user bids.For the functional design,this study introduces a fulltext-retrieval and dispute-processing module for commodities,which reduces the defects existing in the functional module design of existing auction systems.Furthermore,a prototype auction system on the Ethereum test chain is built to validate the proposed scheme.Experiments show that compared with traditional storage methods,indirect storage based on a distributed storage system of texts and images can reduce the storage cost by at least 50%while ensuring data integrity.Finally,the gas cost at each stage of the auction scheme and the time required for the full-text retrieval of products are recorded to evaluate the scheme performance and analyze the test results.

E-Commerce and E-Technology Contribution in Engineeringand Scientific Laboratories Equipments Contracts at JordanianUniversities

This paper presents the role of E-commerce and E-technology in simplifying operations of preparing quotations and contracts of supporting engineering and scientific laboratories by required equipments and tools at Jordanian universities.The experimental and practical sides of education in scientific colleges in Jordanian universities is very important,so many quotations and contacts are performed and required each year,and E-commerce also offers the required information and specifications to persons responsible to do such contacts by using Business-to-Consumer,Consumer-to-Consumer or Business-to-Business principles.By searching about such equipments using search engines,many companies present their products and their specifications and give you the opportunity to select the suitable devices and tools depending on their specifications and prices.Case studies are discussed for some devices to show how much E-commerce simplifies this operation.It was found that E-commerce and E-technology reduces both time and efforts required to support both engineering and scientific labs with their needs from equipments,catalogs and tools required to such devices.