Richard Hobeck, Christopher Klinkmüller, H. M. N. Dilum Bandara, Ingo Weber · 5 authors
Abstract Blockchain technology is known for its transparency properties due to its publicly available, immutable data. Yet, as data availability does not inherently ensure transparency, further analytical methods may be required for human interpretation of data traces. Process mining has emerged as a popular toolbox for understanding processes and how they are executed in practice. The paper studies process mining as a method to enhance the transparency of blockchain data. To this end, two popular Ethereum applications were analyzed using process mining: the prediction and betting marketplace Augur and the network marketing platform Forsage . Observations from the process-mining analyses are used to discuss if process mining can serve as a method to establish transparency of a blockchain. For both applications, new insights are generated for usage scenarios such as application redesign, security analysis, user behavior analysis, and revealing blind spots in Augur’s and Forsage’s documentation. The paper concludes that there is evidence that process mining can serve as a method to enhance transparency in blockchains at the cost of technical setup and knowledge acquisition.
The adoption of smart contracts in decentralized blockchain-based applications enables reliable and certified audits. These audits allow the extraction of valuable information from blockchains, which can be used to reconstruct the execution of the application and facilitate advanced analyses. One of the most commonly used techniques in this context is process mining, which leverages event logs to trace and accurately represent the process execution of applications. However, extracting execution data from blockchains poses significant challenges, and the current methodologies developed have some limitations. Most approaches are tailored to specific use cases, requiring that analysis techniques are defined during the smart contract’s development. Other techniques are applied a posteriori, relying on blockchain events that often lack a standardized format. This absence of standardization requires complex processing steps to correlate logs with the executed actions and such approaches are not universally applicable to all smart contracts on the blockchain , further limiting their scope. Lastly, none of the existing techniques can extract information from event logs embedded in internal transactions of smart contracts. To address these limitations, we propose EveLog an application-agnostic methodology that can be applied to any EVM-compatible application without predefined constraints. Its primary goal is to extract information from smart contracts, capturing both public and internal transactions, and organizing the results into a structured XES event log. The EveLog methodology consists of five key steps: (i) extraction of data from smart contract transactions, (ii) decoding raw data, (iii) selection of sorting criteria, (iv) construction of traces, and (v) generation of the XES event log. EveLog has been implemented in a client–server application and tested on existing solutions, specifically the CryptoKitties application, a blockchain-based game on the Ethereum blockchain. The study was conducted using 12,996 blocks, including over 8000 real transactions from the Ethereum mainnet.
Dan Lin, Jiajing Wu, Yuxin Su, Ziye Zheng · 8 authors
Decentralized bridge applications are important software that connects various blockchains and facilitates cross-chain asset transfer in the decentralized finance (DeFi) ecosystem which currently operates in a multi-chain environment. Cross-chain transaction association identifies and matches unique transactions executed by bridge DApps, which is important research to enhance the traceability of cross-chain bridge DApps. However, existing methods rely entirely on unobservable internal ledgers or APIs, violating the open and decentralized properties of blockchain. In this paper, we analyze the challenges of this issue and then present CONNECTOR, an automated cross-chain transaction association analysis method based on bridge smart contracts. Specifically, CONNECTOR first identifies deposit transactions by extracting distinctive and generic features from the transaction traces of bridge contracts. With the accurate deposit transactions, CONNECTOR mines the execution logs of bridge contracts to achieve withdrawal transaction matching. We conduct real-world experiments on different types of bridges to demonstrate the effectiveness of CONNECTOR. The experiment demonstrates that CONNECTOR successfully identifies 100% deposit transactions, associates 95.81% withdrawal transactions, and surpasses methods for CeFi bridges. Based on the association results, we obtain interesting findings about cross-chain transaction behaviors in DeFi bridges and analyze the tracing abilities of CONNECTOR to assist the DeFi bridge apps.
Asset securitization is an important financial derivative involving complicated asset transfer operations. Therefore, digitizing traditional asset securitization contracts will improve efficiency and facilitate reliability verification. Furthermore, accurate and verifiable requirement description is essential for collaborative development between financial professionals and software engineers. A domain specific language for writing asset securitization contract has been proposed. This solves the problem of difficulty for financial professionals to directly write smart contract by simplifying writing rules. However, due to existing design of the language focused on some simple scenarios, it is insufficient and informal to describe various detailed scenarios. What is more, there are still many reliability issues, such as verifying the correctness of the logical properties of the contract and ensuring the consistency between the contract text and the contract code, within the language in the generation and execution of smart contracts. To overcome the challenges stated above, we extend, simplify and innovate the syntax subset of the domain specific language and name it AS-SC (Asset Securitization – Smart Contract), which can be used by financial professionals to accurately describe requirements. Besides, because formal methods are math-based techniques that describe system properties and can generate programs in a more formal and reliable manner, we propose a semantic consistent code conversion method, named AS2EB, for converting from AS-SC to Event-B, a common and useful formal language. AS2EB method can be used by software engineers to verify requirements. The combination of AS-SC and AS2EB ensures consistency and reliability of the requirements, and reduces the cost of repeated communications and later testing. Taking the credit asset securitization contract as case study, the feasibility and rationality of AS-SC and AS2EB are validated. In addition, by carrying out experiments on three randomly selected real cases in different classic scenarios, we show high-efficiency and reliability of AS2EB method.
Xuling Ye, Ningshuang Zeng, Xingyu Tao, Daguang Han · 5 authors
With the digital transformation of the construction industry, the need to improve construction business process collaboration and automation is increasing. However, as construction projects usually involve many stakeholders with complex relationships and insufficient mutual trust, the existing technologies cannot fulfill the requirements of the construction industry. This paper explores the integration of blockchain, smart contracts, and process automation technologies into construction business processes, shedding light on both managerial and technical challenges. The study introduces a comprehensive technical framework meticulously designed to align with the intricate nature of construction practices while focusing on the resolution of legal complexities associated with smart contract applications and the facilitation of process collaboration and automation. The framework comprises three core modules: (1) action definition and extension to process models, (2) standardized mapping for automatic smart contract generation, and (3) smart contract visualization for reliable process collaboration and automation. This multifaceted approach caters to the specific needs of construction management, standardization, interoperability, and visualization. The framework’s practicality is further evaluated through real-world testing within a construction payment case, effectively showcasing its efficacy and applicability in tangible business scenarios. While this paper represents a significant step forward in addressing construction business process collaboration and automation challenges, it acknowledges the necessity for ongoing research and development to refine and expand these innovative solutions to meet the evolving demands of construction management.
The post-deployment challenges in developing and upgrading blockchain smart contracts necessitate a high level of accuracy in their development and business logic. However, current methodologies for verifying the business logic of smart contracts frequently fail to address their alignment with end-user business requirements. This paper introduces a two-step language transformation process to bridge this gap. Initially, we establish a transformation rule from the Business Process Model and Notation (BPMN) to Prolog, enabling the translation of business processes into a Prolog representation. This step not only validates the business process logic but also ensures it meets user specifications. Subsequently, we introduce a transformation rule from the BPMN to Go, which facilitates the transformation of the BPMN model, once validated, into a Go language smart contract. To enhance usability, we have engineered a dedicated tool that streamlines this transformation process. We present a case study involving a banking loan process to exemplify the utility of our tool in creating BPMN diagrams, conducting requirement and syntax validations, and effecting the transformation to Go smart contracts. The case study and empirical results suggest that our methodology and the accompanying tool mitigate the complexities inherent in smart contract development. They also ensure the fidelity of business logic to user demands, thereby promoting the broader adoption of blockchain smart contract technology.
This study investigates the impact of consensus mechanism changes on cryptocurrency markets within the framework of the efficient market hypothesis, focusing on Ethereum’s transition from Proof-of-Work to Proof-of-Stake consensus, known as the Ethereum 2.0 ‘The Merge’ update. Two main hypotheses guide the enquiry: (i) ‘The Merge’ update will significantly enhance market efficiency and (ii) Ethereum’s updates will have a greater impact on market efficiency compared to other cryptocurrencies. Using the Hurst exponent’s R/S statistic, changes in Ethereum’s long-term memory characteristics before and after major hard forks are quantified. The analysis reveals substantial improvements in Ethereum’s market efficiency following the Ethereum 2.0 hard fork, attributed to the introduction of Proof-of-Stake, which enhanced transaction speed and built trust. These findings suggest a positive trajectory towards improved efficiency in Ethereum’s market, particularly with ‘The Merge’ update. In conclusion, this study contributes to understanding the role of consensus mechanisms in cryptocurrencies and provides insights into future market trends resulting from such changes.
Decentralized autonomous organizations (DAOs) are relatively a newly emerging type of online entity related to governance or business models where all their members work together and participate in the decision-making processes affecting the DAO in a decentralized, collective, fair, and democratic manner. In a DAO, members interaction is mediated by software agents running on a blockchain that encode the governance of the specific entity in terms of rules that optimize their business and goals. In this context, most popular DAO software frameworks provide decision-making models aiming to facilitate digital governance and the collaboration among their members intertwining social and economic concerns. However, these models are complex, not interoperable among them and lack a common understanding and shared knowledge concerning DAOs, as well as the computational semantics needed to enable automated validation, simulation or execution. Thus, this paper presents an ontology (Web3-DAO), which can support machine-readable digital governance of DAOs adding semantics to their decision-making models. The proposed ontology captures the domain logic that allows the sharing of updated information and decisions for all the members that interact with a DAO by the interoperability of their own assessment and decision tools. Furthermore, the ontology detects semantic ambiguities, uncertainties and contradictions. The Web3-DAO ontology is available in open access at https://github.com/Grasia/semantic-web3-dao.
Development of blockchain smart contracts is more difficult than mainstream software development because the underlying blockchain infrastructure poses additional complexity. To ease the developer's task of writing smart contract, as other research efforts, we also use Business Process Model and Notation BPMN modeling to describe application requirements for trade of goods and services and then transform automatically the BPMN model into the methods of a smart contract. In our previous research we described our approach and a tool to Transform Automatically BPMN models into Smart contracts TABS. In this paper, we describe how the TABS approach is augmented with the support for a BPMN collaborative transaction by several actors. Our approach analyzes the BPMN model to determine which patterns in the BPMN model are suitable for use as collaborative transactions. The found BPMN patterns that are suitable as transactions are shown to the developer who decides which ones should be deployed as collaborative transactions. We describe how our approach automatically transform the BPMN model into smart contract the provides a transaction mechanism to enforce the transactional properties of the nested transactions. Our approach greatly reduces the developers task as synchronization of collaborative activities is provided by our approach, so that the developer needs to code only independent tasks with well-defined inputs and outputs. We also overview the TABS+ tool we built as a proof of concept to show that our approach is feasible. Finally, we provide estimates on the cost of supporting the nested BPMN collaborative transactions.
Electronic commerce and finance are progressively supporting and including decentralized, shared and public ledgers such as the blockchain. This is reshaping traditional commercial activities by advancing them towards Decentralized Finance (DeFi) and Commerce 3.0, thereby supporting the latter’s potential to outpace the hurdles of central authority controllers and lawgivers. The quantity and entropy of the information that must be sought and managed to become active participants in such a relentlessly evolving scenario are increasing at a steady pace. For example, that information comprises asset or service description, general rules of the game, and specific technologies involved for decentralization. Moreover, the relevant information ought to be shared among innumerable and heterogeneous stakeholders, such as producers, buyers, digital identity providers, valuation services, and shipment services, to just name a few. A clear semantic representation of such a complex and multifaceted blockchain-based e-Commerce ecosystem would contribute dramatically to make it more usable, namely more automatically accessible to virtually anyone wanting to play the role of a stakeholder, thereby reducing programmers’ effort. However, we feel that reaching that goal still requires substantial effort in the tailoring of Semantic Web technologies, hence this article sets out on such a route and advances a stack of OWL 2 ontologies for the semantic description of decentralized e-commerce. The stack includes a number of relevant features, ranging from the applicable stakeholders through the supply chain of the offerings for an asset, up to the Ethereum blockchain, its tokens and smart contracts. Ontologies are defined by taking a behaviouristic approach to represent the various participants as agents in terms of their actions, inspired by the Theory of Agents and the related mentalistic notions. The stack is validated through appropriate metrics and SPARQL queries implementing suitable competency questions, then demonstrated through the representation of a real world use case, namely, the iExec marketplace.
Edgar Roberto Dulce Villarreal, Julio Ariel Hurtado Alegría, Eduard Antonio Mantilla Torres, Yenny Stella Núñez Álvarez · 5 authors
La tecnología Blockchain está creciendo a un ritmo acelerado en diferentes entornos. Los contratos inteligentes (SC) son programas descentralizados inmutables para plataformas Blockchain que hacen cumplir, monitorear y ejecutar acuerdos, sin la intervención de un tercero de confianza. Pero, debido a sus especificidades, su desarrollo es un proceso complicado, ya que existen restricciones arquitectónicas de cada plataforma, que los desarrolladores deben comprender. En este trabajo, presentamos una herramienta Model Driven Engineering destinada a la generación de SC para la plataforma de Blockchain Ethereum, para el lenguaje de programación Solidity. Esta herramienta está compuesta de un Metamodelo Especifico de la Plataforma y una Transformación de Modelo a Texto, que permiten generar el código fuente de los SC. También, presentamos una prueba de concepto donde generamos e implementamos un metamodelo, un modelo y desplegamos SC en un entorno sanitario. Los resultados son satisfactorios en cuanto a la sintaxis de los SC generados.
Several studies were conducted to demonstrate the application of Process Mining (PM) techniques to Ethereum-compatible application event data. However, the availability of event data is constrained by the application’s process awareness, which is under-reported in the literature. Based on domain analysis, which identified several challenges to mining the business process from blockchain applications, a framework was designed, instantiated, and tested in this study. The framework supports identification of appropriate cases for PM and automates the generation of event logs from blockchain data. It consists of two modules, the Process Awareness Recognizer (PAR) and the Event Log Generator (ELG). PAR is a rule-based classifier to assess the process awareness of a given application. ELG is an automated batch processing model consisting of three methods: (1) Extractor: to retrieve event data from blockchains; (2) Decoder: to transform the extracted data to a human-readable format; and (3) Formatter: to produce event log files in a format compatible with PM tools. It was validated by implementing a proof-of-concept application with an input set of 201 real-world applications. The results prove the framework’s feasibility and applicability.
Muhammad Shoaib Farooq, Hamza Jamil, Hafiz Sohail Riaz
]A multichain non-fungible tokens (NFTs) marketplace is a decentralized platform where users can buy, sell, and trade NFTs across multiple blockchain networks by using cross communication bridge. In past most of NFT marketplace was based on singlechain in which NFTs have been bought, sold, and traded on a same blockchain network without the need for any external platform. The singlechain based marketplace have faced number of issues such as performance, scalability, flexibility and limited transaction throughput consequently long confirmation times and high transaction fees during high network usage. Firstly, this paper provides the comprehensive overview about NFT Multichain architecture and explore the challenges and opportunities of designing and implementation phase of multichain NFT marketplace to overcome the issue of single chain-based architecture. NFT multichain marketplace architecture includes different blockchain networks that communicate with each other. Secondly, this paper discusses the concept of mainchain interacting with sidechains which refers to multi blockchain architecture where multiple blockchain networks are connected to each other in a hierarchical structure and identifies key challenges related to interoperability, security, scalability, and user adoption. Finally, we proposed a novel architecture for a multichain NFT marketplace, which leverages the benefits of multiple blockchain networks and marketplaces to overcome these key challenges. Moreover, proposed architecture is evaluated through a case study, demonstrating its ability to support efficient and secure transactions across multiple blockchain networks and highlighting the future trends NFTs and marketplaces and comprehensive discussion about the technology.
The increasing complexity of decentralized financial systems has necessitated advanced orchestration mechanisms capable of managing dynamic, distributed microservices. Conventional orchestration methods tend to be less flexible, scalable and transparent to support real time financial functions. The proposed paper presents a new Hierarchical Agentic Orchestration architecture, which uses neuro-symbolic intelligence to facilitate the dynamism in composing a workflow in decentralized finance (DeFi) systems. The suggested model uses a multi-level hierarchy of intelligent agents such global, domain and local agents which are coordinated by the use of meta-controller mechanisms. The complex workflows can be broken into parts in this structure and also it promotes real time flexibility. The neuro-symbolic layer unites machine learning predictive analytics models with symbolic rule enforcement and compliance with a need to ensure flexibility and interpretability. Moreover, the blockchain and smart contract offer a level of trust, immutability, and auditability, which solve the essential issues of decentralized systems. The implementation is carried out on the microservices-based architecture with an event-driven communication channel, which allows workflow execution to be scaled and resilient. The experimental findings show that there are significant latency, throughput, and accuracy improvements with experimental techniques as opposed to the conventional techniques of orchestration. The system is also highly adaptable to the dynamic load and keeps within the predefined policies. On the whole, the study introduces an all-encompassing and intelligent orchestration paradigm that promotes efficiency, transparency, and reliability of decentralized financial ecosystems, which is the foundation of next-generation autonomous financial systems.
Blockchains and distributed ledger technology offer promising capabilities for supporting collaborative business processes across organizations. Typically, approaches in this field fall into two categories: either executing the entire process model on the blockchain or using the blockchain primarily to enforce or monitor the exchange of messages between participants. Our work proposes a novel approach that sits between these two methods. We introduce a centralized process model extended with blockchain annotations, detailing the tasks of each participating organization and the extent to which blockchain technology is needed to secure task execution. This model also includes all critical data objects and specifies how their handling should be protected by the blockchain. This technical report outlines a systematic three-step method for automatically decentralizing this comprehensive model into individual local process models for each organization, coupled with a separate process model for the blockchain. This decentralized structure effectively replicates the original global process model. Our transformation approach is rule-based, focusing on creating a platform-inde-pendent model first, then a platform-specific model. Subsequently, we project the platform-specific model to obtain one model for the blockchain and one model for each participating organization.
Juanjuan Li, Xiaolong Liang, Rui Qin, Fei–Yue Wang
As the key component of the emerging Web3, Decentralized Autonomous Organizations and Operations (DAOs) enables decentralized decision-making and governance mainly driven by blockchain and smart contracts. This paper first provides a comprehensive examination of DAOs’ evolution, tracing their historical development and the progression of their definitions and underlying concepts. Then, it presents their classical governance models founded on token economics and analyzes typical practical cases, subsequently identifying the current dilemmas faced by DAO governance. To address these dilemmas, TRUE Autonomous Organizations and Operations (TAOs) are proposed, which underscores the trustable, reliable, usable, efficient and effective essence of decentralization. Besides, the distinctions between TAOs and DAOs are discussed from perspective of the value systems, governance structures, incentive allocation, decision-making model. Furthermore, it highlights the research issues that need to be addressed to realize the full potential of TAOs.
This article conducts an extensive examination of the persisting challenges related to smart contract attacks within blockchain networks, with a particular focus on the reentrancy attack. It emphasizes the inherent vulnerabilities embedded in the programming languages commonly employed for smart contract development, particularly within Ethereum Virtual Machine (EVM)-based blockchains. While the concrete example used primarily employs the Solidity programming language, the insights garnered from this study are readily generalizable to a wide array of blockchain architectures. Significantly, this article extends beyond the mere identification of vulnerabilities and ventures into the realm of proactive security measures. It explores the adaptation and adoption of dataflow programming paradigms, employing Domain-Specific Languages (DSLs) to enforce security by design in the context of smart contract development. This forward-looking approach aims to bolster the foundational principles of blockchain security, offering a promising research direction for mitigating the risks associated with smart contract vulnerabilities. The objective of this article is to cater to a diverse audience, ranging from individuals with limited computer science and programming expertise to seasoned experts in the field. It provides a comprehensive and accessible resource for fostering a deeper understanding of the intricate dynamics between blockchain technology and the imperative need for secure smart contract development practices.
With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITS.
Vimal Dwivedi, Mubashar Iqbal, Alex Norta, Raimundas Matulevičius
Blockchain governs inter-organizational business processes and enables decentralized autonomous organizations (DAO) with governance capabilities via smart contracts (SC). Due to the programmer’s lack of prior knowledge of the contract domain, SCs are ambiguous and error-prone. Several works, i.e., SPESC, Symboleo, and SmaCoNat, exist to support the legally-binding SCs. The aforementioned SCLs present intriguing approaches to building legally-binding SCs but either lack domain completeness, or are intended for non-collaborative business processes. In our previous work, we address the above-mentioned shortcomings of the XML-based smart-legal-contract markup language (SLCML), in which blockchain developers focus on the contractual workflow rather than the syntax specifics. However, SLCML, as a blockchain-independent formal specification language, is not evaluated to determine its applicability, usefulness, and usability for establishing legally-binding SCs for workflow enactment services (WES) to automate and streamline the business processes within connected organizations. In accordance with this, we formally implement the SLCML and propose evaluation approaches, such as running case and lab experiments, to demonstrate the SLCML’s generality and applicability for developing legally-binding SCs. Overall, the results of this work ascertain the applicability, usefulness, and usability of the proposed SLCML for establishing legally-binding SCs for WES.
Julião Braga, Francisco Regateiro, Itana Stiubiener, Juliana Cristina Braga
This work presents a manually built ontology to aggregate and knowledge systematization of Decentralized Autonomous Organizations (DAOs) obtained from web pages. An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships between them, providing a common vocabulary for researchers to share information. Ontology construction from text involves analyzing collected text, identifying relevant terms and concepts, and representing the ontology using representation languages such as OWL, RDF, or RDFS. Manual ontology construction can be performed using applications such as Protege. This work describes the methodology used, how to use the ontology created through Protege using SPARQL, and presents future work proposals, including creating the same ontology using Deep Learning from Machine Learning techniques.