Blockchain-based Smart Contracts Research Articles

DETECTING AND PREVENTING FINANCIAL RESTATEMENTS USING BLOCKCHAIN BASED SMART CONTRACT: THE CASE OF THE EGYPTIAN COMPANIES

Financial restatements pose a significant problem for companies and stakeholders. Accurate financial information is therefore critical to decision making, and preventing restatements is vital to maintaining the confidence of shareholders, investors, and other stakeholders. In this paper, a quantitative study utilizing a survey to determine the causes and consequences of the financial restatements applied to the Egyptian context. Based on the survey’s results, a proposed architecture was presented to detect and prevent financial restatements using blockchain-based smart contracts. The proposed architecture is implemented based on Remix - Ethereum IDE, with a consortium blockchain, and it consists of three layers, which are the presentation layer, detection and prevention layer, and blockchain layer. All layers are integrated using APIs to detect and prevent restatement caused by accounting errors, reclassification of accounting items, and intentional misstatement, and to inform all various stakeholders of any detected cases. The proposed implemented architecture is tested by a sample of data collected from some Egyptian list companies. According to testing results, it can work in real environments with an accuracy rate of up to 97.5%. The findings of this study are pertinent to listed companies, shareholders, investors, banks, credit institutions, and other stock market regulators, as financial restatements negatively affect a company’s credibility in its financial reporting. The findings extend both the literature on the role of blockchain technology in preventing financial restatements and the literature on experimentally implementing blockchain technology in the Egyptian context.

A Systematic Literature Review on Blockchain-based Smart Contracts: Platforms, Applications, and Challenges

Blockchain technology has rapidly emerged with a multitude of applications, among which smart contracts have garnered considerable attention. Smart contracts represent a promising solution for streamlining trade and business transactions between untrusted parties without intermediaries. These self-executing pieces of code automatically execute predefined actions when specific conditions are met. Despite the growing enthusiasm for blockchain and smart contracts, researchers believe this powerful combination has not yet reached its full potential. Hence, a systematic study is conducted to explore the various facets of blockchain-based smart contracts comprehensively. The research follows the PRISMA framework and employs two primary approaches: bibliometric analysis and systematic literature review. The process was initiated by formulating targeted search queries within the Scopus database, identifying a total of 1,949 publications spanning from January 2019 to August 2023. Subsequently, a bibliometric analysis was conducted on these publications using VOSViewer and Biblioshiny. Further, the full text of these publications was meticulously screened to isolate those with a significant focus on smart contracts. This led to the identification of 48 publications, each offering unique insights into various smart contract applications. Upon further examination, it was observed that the majority of these publications held rankings within the China Computer Federation, which refers to the qualitative research work in this domain. The study concludes with the current state of blockchain-based smart contracts, their platforms, applications, and challenges and reveals the substantial potential in handling tasks with predefined conditions and security requirements.

An API Security Framework for IoT-Enabled Healthcare System with the Application Blockchain-Based Smart Contract

An API Security Framework for IoT-Enabled Healthcare System with the Application Blockchain-Based Smart Contract

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

Unfortunately, within the framework of blockchain contracting, a significant gap exists in comprehending contractual behavior, and the feasibility of predictive contracts has largely remained unexplored. A principal obstacle stems from the absence of a seamless integration between predictive concepts and blockchain technology. This deficiency is attributed to a failure to consider the inherent characteristics of blockchain when developing solutions aimed at improving predictive capabilities within blockchain-based systems. Many existing predictive approaches function externally to the fundamental blockchain framework, rendering them impractical. This has caused the idea of predictive contracts to be seen as unfeasible due to the character of blockchain smart contracts making it hard to do so. This includes its immutability and the inability for changes to be made once deployed. In this research, we introduce the concept of blockchain-based predictive contracting which stems from the theoretical idea of predictive contracting, and substantiate the feasibility of our approach, enabling blockchain smart contracts to adapt to changes in external environments upon which they depend. We attempt to achieve and prove the first phase of this idea, which we term “recalibration”. Here we provide a means for deployed smart contracts to become structurally changeable while responding to external situations without compromising their security. This we believe is the first phase needed for blockchain smart contracts before they can become predictable. Our approach capitalizes on the key-pair structure scheme utilized in existing blockchain systems to create a data signature, facilitating the identification of new smart contracts. We establish rules encompassing a configuration mechanism, empowering smart contracts to recognize newly-introduced agreements. Additionally, we implement an encoding system to enable the blockchain to respond to dynamic data. This we believe will provide a means for blockchain to be used well in industrial applications such as supply aircraft delivery networks and supply chain networks. To anticipate future scenarios, we devise a multi-versioning system that allows smart contracts to evolve over time. Our innovative concept is also demonstrated within a blockchain-based smart contract prediction scheme, ensuring the adaptability of blockchain-based smart contracts. This scheme comprises a smart contract tracing mechanism, an effective smart contract transitioning procedure, and a protocol for generating new smart contracting terms and conditions while preserving inherent trust within the system. Through extensive experimentation, involving opcode and smart contract ID extraction, Solidity Word2Vec model development, a blockchain-based embedding process, and smart contract versioning detection, we introduce the concept of blockchain-based predictive smart contracts. Notably, we observe a significant enhancement as multiple parties engage in complex operations on the blockchain, with an average gas cost of 31374215 Wei for demonstrating smart contractual operations within exogenous conditions. This validates the cost efficiency of our approach over prior methods. Our empirical results affirm the novelty and efficacy of our proposed concept.

Transforming agri-food value chains in Bangladesh: A practical application of blockchain for traceability and fair pricing

The agricultural sector is a vital component of Bangladesh's economy, but its agri-food supply chain faces signifi-cant inefficiencies primarily due to the involvement of numerous intermediaries. This complexity not only reduces the profits for farmers but also affects the overall transparency and efficiency of the supply chain. This study aims to em-ploy blockchain technology to transform the traditional agri-food supply chain in Bangladesh, focusing on increasing transparency, enhancing efficiency, and improving profitability for farmers, thus potentially bolstering the entire agri-food ecosystem in the country. The research involves setting up a blockchain-based smart contract on the Ethereum Blockchain network. This approach guarantees that all transactions within the agri-food supply chain are transparent, traceable, and accountable. Additionally, the study develops a web application to facilitate user interaction with the smart contract, enhancing accessibility and usability. Performance analysis and testing of the implemented smart con-tract demonstrate its capability to handle a significant volume of transactions without compromising on performance. The solution effectively reduces the dependency on intermediaries, thereby increasing the profit margins for the farm-ers involved. The integration of blockchain technology in the agri-food supply chain has shown promising results in enhancing transparency and efficiency. It lays a solid foundation for future improvements and suggests a scalable model that could be applied to other sectors within the country to further enhance agricultural practices and economic growth.

Secure Blockchain Assisted Attribute-Based Keyword Search for Collaborative E-Healthcare

In the age of technological advancement, collaborative E-healthcare emerges as a transformative system eliminating traditional location and accessibility barriers in healthcare services. Here, Searchable Encryption (SE) plays a key role in enabling healthcare providers to outsource encrypted medical data and search services to third parties like cloud servers, thereby reducing storage and management expenses. This intermediary approach poses challenges of single-point failure, privacy breaches, and potentially untrustworthy results. State-of-the-art public key-based SE methods use a cloud-assisted architecture that doesn’t support reliable and practical searches with fine-grained permissions. Also, such systems require additional support to address potential privacy leakages and ensure data availability at the storage server. To address these concerns, we propose a B lockchain-assisted E fficient and S ecure K eyword S earch (BESKS) scheme to enforce fine-grained keyword search privilege control while achieving practical search complexity. Our scheme employs a ciphertext policy attribute-based keyword search mechanism where keywords are encrypted using expressive access policies to build an inverted index structure. The encrypted indexes are stored on the blockchain while encrypted medical documents are stored on InterPlanetary File System (IPFS) nodes to enhance availability and ensure the reliability and scalability of our approach. Our scheme utilizes blockchain-based smart contract for efficient, secure search operations and ensures financial fairness in fine-grained searches. Search tokens are generated based on user attributes and query keywords to facilitate private searches on-chain. To enhance the search process, our secure index enables exact match for a query keyword in constant time to ensure expensive authorization operations are performed only once. Theoretical analysis suggests that our BESKS is more efficient and secure than state-of-the-art schemes. Prototype implementation results on the Ethereum blockchain network further validate its feasibility for real-world applications, demonstrating the scheme's practical applicability in collaborative E-Healthcare systems.

Analysis of Implementation of Anti-Money Laundering Mechanisms in Blockchain-Based Smart Contracts under Indonesian Regulation

One of the most widely adopted forms of information technology application today is electronic trade through the internet network to make transactions. This transaction system was initially centralized, but with the risk of system failure and hacking, distributed systems such as blockchain were developed to improve security and efficiency. Blockchain also gave birth to derivative technologies such as smart contracts, automated blockchain-based digital agreements. Despite offering many advantages, the anonymity and decentralization of smart contracts raise concerns of misuse for illicit activities such as money laundering. Therefore, regulatory updates in Indonesia are needed to regulate the validity of smart contracts and money laundering actions through this technology. This article analyses the validity and regulation of smart contracts and efforts to implement the AML system in blockchain-based transactions in Indonesia.

A Study on the Legal Status of Blockchain-Based Smart Contracts

A Study on the Legal Status of Blockchain-Based Smart Contracts

MDAPW3: MDA-based development of blockchain-enabled decentralized applications

Web3.0 Decentralized Application (DApp) is a class of decentralized software in which at least the business logic of the software is implemented using blockchain-based smart contracts. Features such as transparency, decentralized execution environment, no need for a central authority, immutability of data from manipulation, as well as a native transaction-based payment system based on cryptographic tokens are the main advantages of Web3.0 DApps over conventional Web2.0 software in which the business logic and user data are centrally controlled by companies with no transparency. However, the development lifecycle of Web3.0 DApps involves many challenges due to the complexity of blockchain technology and smart contracts as well as the difficulties concerning with the integration of DApp on-chain and off-chain components. To alleviate these challenges, a Model Driven Architecture (MDA) approach for the development of Web3.0 DApps is proposed in this paper that streamlines the development of complex multi-lateral DApps and results in a product that is verifiable, traceable, low-cost, maintainable, less error-prone and in conformance with blockchain platform concepts. Opposed to previous studies in this area that applied MDA only for the development of smart contracts, our proposed MDA-based approach covers the full architecture of Web3.0 DApps: on-chain, off-chain and on-chain/off-chain communication patterns. The method application was demonstrated by implementing a land leasing Dapp where the requirement model (a BPMN choreography model) was transformed into CIM, PIM, and PSM instances successively, and finally, the code-base was generated based on the Ethereum platform technology stack. Epsilon Validation Language (EVL), Epsilon Object Language (EOL), and Epsilon Comparison Language (ECL) were used for the verification/validation of the model instances at each step. Furthermore, by evaluating the quality metrics of the proposed meta-models, we show that they have a better ontology coverage and are more reusable and understandable compared to previous meta-models.

Cooperation Among Strangers: Algorithmic Enforcement of Reciprocal Exchange with Blockchain-Based Smart Contracts

Cooperation Among Strangers: Algorithmic Enforcement of Reciprocal Exchange with Blockchain-Based Smart Contracts

Decentralised autonomous organisations: targeting the potential beyond the hype

ABSTRACT Decentralised Autonomous Organisations (DAOs) aim at innovating the organisation forms for business activities. They are complex blockchain-based smart contracts, which allow token holders to participate directly in decision-making processes and decentralised entrepreneurial activities as much as possible. The advocates of this new kind of digital organisation argue that DAOs enjoy significant operational efficiencies and can effectively work outside of any legal recognition. This paper analyses DAOs through the lenses of the economic and legal theories on the firm and on business organisation. The analysis makes three contributions: first, it contributes to the literature on the theory of the firm, looking at the role of digital technology in innovating the organisation of business activities. Second, it enriches the literature on the legally recognised forms of business organisation, analysing the tension between the essential role of the law and the limitations of tamper-resistant technologies, such as the blockchain. Third, it overcomes the largely ideological and dichotomic debate on the promises of DAOs, providing analytical guidelines as to why current forms of sector-specific regulation fail to leverage the potential of DAOs.

APPLICATION OF SMART CONTRACTS IN ELECTRONIC SYSTEMS BASED ON BLOCKCHAIN TECHNOLOGIES

In the era of digitization, where information technology and business processes are closely intertwined, the development and implementation of blockchain-based smart contracts become key to achieving a new level of automation, security, and efficiency. This article deeply analyzed how blockchain smart contracts can enhance the execution of contractual obligations, making processes more transparent and efficient. The main aspect of study is the technical details of smart contracts and exploration of their practical application for optimizing business procedures, significantly reducing risks associated with fraud and the need for intermediaries. A practical demonstration of deploying a smart contract, executed in the Python programming language, is proposed as a method used in the article, highlighting the possibilities and challenges related to scalability and regulation. Results underscore a notable boost in operational efficiency and security, while also identifying barriers to broader technological adoption. Concluding, the significant role of smart contracts in evolving information systems is underlined, advocating for novel approaches to secure, autonomous contract fulfillment and emphasizing the importance of ongoing research to exploit their full capabilities in fortifying information security and operational efficacy.

Kaizen: A Street Smart Low Latency-Aware Resource Choreography Scheme for Decentralized Autonomous Organization (DAO) and Non-DAO Based Application Execution Over Blockchain and MEC Empowered 6 G Network

Decentralized autonomous organization (DAO)-based applications can revolutionize traditional centralized decision-making procedures and services by enabling scalable, decentralized, autonomous, and democratized decision-making processes. Unlike traditional applications, DAO-based decentralized applications use Ethereum blockchain-based smart contract programs to execute policies or make automated decisions. To that end, 6 G technologies can improve the latency and reliability of many existing blockchain-based DAOs. Previous research did not investigate the execution of DAO and non-DAO-based applications, as well as an adaptive resource choreography scheme, while accounting for various 6 G technologies, blockchain, and mobile-edge cloud (MEC). To prevail over the previous shortcomings, this article supplies a street smart multi-platform coordination, application scheduling, and low-latency-aware resource choreography scheme for both DAO and non-DAO-based application execution over blockchain and MEC-enabled 6 G networks by taking heterogenous DAO and non-DAO application count, application requirements, physical worker, virtual worker, and communication resource status into account. The results verified that the proposed kaizen scheme delivers at least 11.26% app work completion delay gain, 7.2% user energy overhead gain, 6.55% user economic charge gain, and 21% service provider profit than the compared schemes.

Privacy-Preserving Byzantine-Resilient Swarm Learning for E-Healthcare

An automatic medical diagnosis service based on deep learning has been introduced in e-healthcare, bringing great convenience to human life. However, due to privacy regulations, insufficient data sharing among medical centers has led to many severe challenges for automated medical diagnostic services, including diagnostic accuracy. To solve such problems, swarm learning (SL), a blockchain-based federated learning (BCFL), has been proposed. Although SL avoids single-point-of-failure attacks and offers an incentive mechanism, it still faces privacy breaches and poisoning attacks. In this paper, we propose a new privacy-preserving Byzantine-resilient swarm learning (PBSL) that is resistant to poisoning attacks while protecting data privacy. Specifically, we adopt threshold fully homomorphic encryption (TFHE) to protect data privacy and provide secure aggregation. And the cosine similarity is used to judge the malicious gradient uploaded by malicious medical centers. Through security analysis, PBSL is able to defend against a variety of known security attacks. Finally, PBSL is implemented by uniting deep learning with blockchain-based smart contract platforms. Experiments based on different datasets show that the PBSL algorithm is practical and efficient.

Synergizing AI and Blockchain: Innovations in Decentralized Carbon Markets for Emission Reduction through Intelligent Carbon Credit Trading

This study aims to enhance the paradigm of decentralized carbon markets by proposing an innovative integration of artificial intelligence (AI) and blockchain technology for intelligent carbon credit trading with the goal of attaining sustainable emission reduction. Blockchain systems powered by artificial intelligence (AI) have the potential to boost the effectiveness of current systems and expedite the global implementation of emissions trading. Although still in its infancy, blockchain artificial intelligence (AI) presents a promising solution to some of the world's most pressing environmental issues. Environmental sustainability is greatly affected by artificial intelligence because of its decentralized computation architecture. The Artificial Intelligence and blockchain are outstanding direction for today’s environmental issues starting from carbon footprint emission to earth market unstable management, whereby the AI facilitates the best possible operational control of power systems and the blockchain offers decentralized trading platforms for the energy markets. The paper's theoretical framework, based on advanced mathematical models, serves as the foundation for this study, in which AI algorithms are methodically constructed to anticipate carbon emissions with unprecedented accuracy. Using sophisticated coding simulations and complicated mathematical formulas, the study boldly transitions into a realistic digital implementation that builds on this theoretical foundation. This complex experiment not only validates the theoretical ideas but also illustrates the complex relationship between blockchain and AI in the decentralized carbon market ecosystem. This experiment's mathematical basis is the creation of an integrated pricing model that seamlessly blends blockchain-based trading dynamics with AI-driven forecasts. The model incorporates a dynamic, self-adjusting system that responds to current market conditions, in addition to optimizing the pricing calculation of carbon credits. Complex market dynamics, player tactics, and the overall equilibrium of the carbon credit market are all modeled by mathematical simulations. The project goes deeper into building blockchain-based smart contracts, which enable safe and transparent transactions. The comprehensive mathematical results of the experiment shed light on the best way to price carbon credits while underscoring the disruptive potential of blockchain and artificial intelligence in terms of sustainable emission reduction strategies used in carbon markets. Major conclusions about the potential advantages of Blockchain AI for guaranteeing emissions reduction are drawn from the current study. Additionally, it presents a roadmap for future research in this area.

Transaction Security and Management of Blockchain-Based Smart Contracts in E-Banking-Employing Microsegmentation and Yellow Saddle Goatfish

The process security of money transactions is considered an important issue in e-banking. Additionally, it is an enormous problem if never controlled. particular, security should be a combination of fast and sturdy characteristics, which is the subject of previous studies suffered from. Our research attempts to improve the system in which banks deal with the security of financial transactions. This research leverages the idea of microsegmenting the entire system into designated zones to concentrate on security, where each zone has its own rules and limitations. These rules are managed by a smart contract, which decides whether they have been observed to verify the legitimacy of the customer. First, the two-phase commit algorithm (2PC) was used to specify the type of e-banking request. After this, the microsegmentation principle was applied to isolate each type of e-transaction process alone in a separate segment. Then, the yellow saddle goatfish algorithm (YSGA) was used to determine whether the smart contract conditions were optimized. Finally, if the customer is authorized, then the entire transaction process is saved in the blockchain's main ledger and secured by a unique hash. The blockchain application makes our system capable of dealing with large numbers of users in a decentralized manner. In addition, using a hash with each block prevents fraudulent transactions by adversaries. Our system has been examined against several recent well-known assaults/attacks, such as falsification, advanced persistent threat, bribery, spoofing, double spending, chosen text, race, and transaction replay attacks, and has proven to overcome them. In terms of the performance evaluation, we obtained an execution time of approximately 0.0056 nanoseconds, 3.75% complexity, and 1500 KB of memory and disk drive, which is considered low compared to that of state-of-the-art research. Thus, our proposed system is highly acceptable for banking sector applications.

Realtime polymorphic malicious behavior detection in blockchain-based smart contracts

Abstract This paper proposes an innovative approach to achieving real-time polymorphic behavior detection, and its direct application to blockchain-focused smart-contracts. We devise a method based on a non-deterministic finite state machine to perform approximate pattern-matching, using a look-ahead mechanism implemented through a concept similar to that of a sliding window, and using threshold-based similarity checking at every state in the automaton. We introduce and formalize our approach, discuss the challenges we faced and then test it in a real-world environment. The experimental results obtained showed a significant speed-up of our approach, as compared to the classic similarity measures used commonly in such scenarios.

Multi-agent-based decentralized residential energy management using Deep Reinforcement Learning

In smart grid, energy consumption has grown exponentially in residential houses, which necessitates the adoption of demand response management. To alleviate and handle the energy management in residential houses, an efficient residential energy management (REM) system can be employed to regulate the energy consumption of appliances for several energy loads such as non-shiftable, shiftable, and controllable loads. Many researchers have focused on the REM using machine learning and deep learning techniques which is not able to provide secure and optimal energy management procedure. Thus, in this paper, a multi-agent-based decentralized REM, i.e., MD-REM approach is proposed using Deep Reinforcement Learning (DRL) with the utilization of blockchain. Furthermore, The combinatorial model DQN, i.e., Q-learning and deep neural network (DNN) is employed, to gain the optimal price based on the reduced energy consumption by appliances associated with different energy loads utilizing the Markov Decision Process (MDP). Here, multiple agents are designed to handle different energy loads and consumption is controlled by the DQN agent, then reduced consumption data is securely shared among all stakeholders using blockchain-based smart contract. The performance evaluation of the proposed MD-REM approach seems to be efficient in terms of reduced energy consumption, optimal energy price, reward, and total profit analysis. Moreover, blockchain-based result is evaluated for the proposed MD-REM approach considering the performance metrics such as transaction efficiency, Interplanetary File System (IPFS) bandwidth utilization, and data storage cost comparison.

Legality of Blockchain and Smart Contracts in India

India is presently experiencing a moment of profound transformation that encompasses revisions to its constitution and legal principles. In this era of remarkable transformation, it would be imprudent to overlook the technological innovations and digital advancements that have permeated the legal domain. One particularly vital aspect in this context is the field of Contract Law. Presently, electronic contracts in India are primarily governed by The Indian Contract Act, in conjunction with the Information Technology Act and the Indian Evidence Act, unless stated otherwise. These legal frameworks provide the foundation for legally enforceable electronic contracts in the country. This research paper emphasizes the urgent requirement for a legal adaptation in the field of Contract Law to align with the ever-evolving technological landscape. It also delves into the legal intricacies associated with blockchain-based Smart Contracts, elucidating how these contracts function within the current judicial landscape. Finally, it concludes by emphasizing the necessity for a pioneering effort to regulate this dynamic domain.

Collaboration of Heterogeneous Edge Computing Paradigms: How to Fill the Gap Between Theory and Practice

Edge computing paradigms such as cloudlet, mobile edge computing (MEC) and fog computing, are promising to reduce network transmission delay while meeting intensive computing requirements at the network edge. As always assumed in theoretical studies, to expand service capability, it is desirable to integrate edge resources into a unified resource pool and make different edge facilities collaborate. However, this collaboration is difficult in practice since the heterogeneity among paradigms leads to resource isolation. This article focuses on clarifying and shielding heterogeneity among edge computing paradigms for collaboration. First, based on cloudlet, mobile edge computing and fog computing, three main edge computing paradigms, i.e., small cloudy edge paradigm (SmallC), mobile integrated edge paradigm (MobInt) and front ad hoc edge paradigm (FrontAH), are defined. So that the heterogeneity among them can be analyzed, according to which, collaboration challenges in computing resource trading, information communication and resource sharing are identified. Promising techniques such as blockchain-based smart contract, media-independent handover (MIH), and software-defined network and network function virtualization (SDN/NFV) are then introduced and integrated into a complete collaboration solution. Finally, taking the unmanned vehicular navigation as an example, the performance of collaboration is evaluated, considering additional costs introduced by collaborations, including trading, network handoff and data transmission among edge facilities in different paradigms. Simulation results show that compared with existing schemes of the three paradigms, the collaboration can reduce the cost (i.e. weighted sum of energy consumption and delay) by at least 45.6%.