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Through its smart contract capabilities, blockchain has become a technology for automating cross-organizational processes on a neutral platform. Process mining has emerged as a popular toolbox for understanding processes and how they are executed in practice. While researchers have recently created techniques for the challenging task of extracting authoritative data from blockchains to facilitate the analysis of blockchain applications using process mining, as yet there has been no clear evaluation of the usefulness of process mining on blockchain data. With this paper, we close that gap with an in-depth case study of process mining on the popular Ethereum application Augur, a prediction and betting marketplace. We were able to generate value-adding insights for application-redesign and security analysis, as validated by the application's chief architect and revealed blind spots in Augur's white paper.
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... In the process mining area, some work has been done to apply it to the blockchain. In [56], the authors used process mining techniques to specify the behavior of the Augur protocol, discovering bottlenecks and proposing improvements. Some tools to automatize the creation of process models from blockchain protocols to facilitate multiple goals have been proposed [57]- [60], but none for the cross-chain scenario. ...
Preprint
p>Ecosystems of multiple blockchains are now a reality. Multi-chain applications and protocols are perceived as necessary to enable scalability, privacy, and composability. Despite being a promising emerging research area, we recently have witnessed many attacks that have caused billions of dollars in losses. Attacks against bridges that connect chains are at the top of such attacks in terms of monetary cost, and no apparent solution seems to emerge from the ongoing chaos. In this paper, we present our contribution to minimizing bridge attacks. In particular, we explore the concepts of cross-chain transaction, cross-chain logic, and the cross-chain state as the enablers of the cross-chain model. We propose Hephaestus , the first cross-chain model generator that captures the operational complexity of cross-chain applications. Hephaestus can generate cross-chain models from local transactions on different ledgers realizing arbitrary use cases and allowing operators to monitor their cross-chain applications. Monitoring helps identify outliers and malicious behavior, which can help programmatically to stop bridge hacks and other attacks. We conduct a detailed evaluation of our system, where we implement a cross-chain bridge use case. Our experimental results show that Hephaestus can process 600 cross-chain transactions in less than 5.5 seconds in an environment with two blockchains and requires sublinear storage.</p
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Conditional payments allow the transfer of money only when predefined rules hold. Example uses could include welfare payments, employee expenses, insurance payouts, or tied donations. Normally, conditions are checked manually in reimbursement or pre-approval/audit processes, either at accounts before funds are distributed, or using account records after distribution. Blockchain's capabilities for smart contract and digital assets can be used to implement next-generation conditional payments, on a decentralized ledger. We conducted a project with an industry partner where we conceptualized, implemented, and evaluated a novel programmable money concept using blockchain. In the system, programmed policies are not attached to accounts , but instead to money itself. Policies here specify under which conditions money may be spent, and can be automatically checked by the money as it is spent. Policies can be dynamically added to and removed from money as it flows through an economy. Here we report on some of our experiences and insights regarding blockchain architecture, software engineering with blockchain, and blockchain-based programmable money. Selected open research questions are listed at the end of the paper.
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Process mining techniques use event data to show what people, machines, and organizations are really doing. Process mining provides novel insights that can be used to identify and address performance and compliance problems. In recent years, the adoption of process mining in practice increased rapidly. It is interesting to see how ideas first developed in open-source tools like ProM, get transferred to the dozens of available commercial process mining tools. However, these tools still resort to producing Directly-Follows Graphs (DFGs) based on event data rather than using more sophisticated notations also able to capture concurrency. Moreover, to tackle complexity, DFGs are seamlessly simplified by removing nodes and edges based on frequency thresholds. Process-mining practitioners tend to use such simplified DFGs actively. Despite their simplicity, these DFGs may be misleading and users need to know how these process models are generated before interpreting them. In this paper, we discuss the pitfalls of using simple DFGs generated by commercial tools. Practitioners conducting a process-mining project need to understand the risks associated with the (incorrect) use of DFGs and frequency-based simplification. Therefore, we put these risks in the spotlight.
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The auditing sector is acquiring a strong interest in the diffusion of blockchain technologies. Such technologies guarantee the persistence, and authenticity of transactions related to the execution of a contract, and then enable auditing activities. In particular, they make possible to check if observed sequences of transactions are in line with the possibly expected ones. In other words, auditing blockchain transactions allow users to check if the smart contract fits the expectation of the designers, that for instance could check if a given activity is performed or if it satisfies a given set of properties. In such a setting we propose a methodology that exploits process mining techniques to evaluate smart contracts, and to support the work of the auditor. Models resulting from the mining can be used to diagnose if the deployed application works as expected, and possibly to continuously improve them. We illustrate the use of our approach using a small, but real, case study.
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The integration of business process management with blockchains across organisational borders provides a means to establish transparency of execution and auditing capabilities. To enable process analytics, though, non-trivial extraction and transformation tasks are necessary on the raw data stored in the ledger. In this paper, we describe our approach to retrieve process data from an Ethereum blockchain ledger and subsequently convert those data into an event log formatted according to the IEEE Extensible Event Stream (XES) standard. We show a proof-of-concept software artefact and its application on a data set produced by the smart contracts of a process execution engine stored on the public Ethereum blockchain network.
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Blockchain technology opens up new opportunities for Business Process Management. This is mainly due to its unprecedented capability to let transactions be automatically executed and recorded by Smart Contracts in multi-peer environments, in a decentralised fashion and without central authoritative players to govern the workflow. In this way, blockchains also provide traceability. Traceability of information plays a pivotal role particularly in those supply chains where multiple parties are involved and rigorous criteria must be fulfilled to lead to a successful outcome. In this paper, we investigate how to run a business process in the context of a supply chain on a blockchain infrastructure so as to provide full traceability of its run-time enactment. Our approach retrieves information to trace process instances execution solely from the transactions written on-chain. To do so, hash-codes are reverse-engineered based on the Solidity Smart Contract encoding of the generating process. We show the results of our investigation by means of an implemented software prototype, with a case study on the reportedly challenging context of the pharmaceutical supply chain.
Book
This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment. The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives. Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments. “If your organization cares about operational performance and has a culture that thrives on transparency, Process Mining is the answer to your prayers. And there is no better source than this book to learn about what Process Mining is, how it's being used in leading companies, and where it might go in the future.” Thomas H. Davenport (Distinguished Professor, Babson College and Research Fellow, MIT Initiative on the Digital Economy); Author of Process Innovation, Competing on Anal “Unlike the traditional plan-execution process improvement, Process Mining allows full transparency of actual processes and activities. Process Mining in Action describes principles, challenges and learnings from years of practice.” Seungjin Whang (Professor of Operations, Information & Technology at Stanford Graduate School of Business) “This is a timely book that presents operational experiences and brings Process Mining application problems to academic research communities. It inspires researchers to further develop frameworks and techniques to tackle broader process analytics challenges over multiple application domains in order to complement the fast growing operational community.” Jianwen Su (Professor of Computer Science at University of California, Santa Barbara) Features and Benefits First book to present an overview of successful industrial experiences of process mining Operational experts describe use cases and business impact along the whole value chain Discusses the challenges, lessons learned and failures in order to provide guidance on how to avoid pitfalls and ensure successful operational deployment
Book
This book addresses what software architects and developers need to know in order to build applications based on blockchain technology, by offering an architectural view of software systems that make beneficial use of blockchains. It provides guidance on assessing the suitability of blockchain, on the roles blockchain can play in an architecture, on designing blockchain applications, and on assessing different architecture designs and tradeoffs. It also serves as a reference on blockchain design patterns and design analysis, and refers to practical examples of blockchain-based applications. The book is divided into four parts: Part I provides a general introduction to the topic and to existing blockchain platforms including Bitcoin, Ethereum, and Hyperledger Fabric, and offers examples of blockchain-based applications. Part II focuses on the functional aspects of software architecture, describing the main roles blockchain can play in an architecture, as well as its potential suitability and design process. It includes a catalogue of 15 design patterns and details how to use model-driven engineering to build blockchain-based applications. Part III covers the non-functional aspects of blockchain applications, which are cross-cutting concerns including cost, performance, security, and availability. Part IV then presents three detailed real-world use cases, offering additional insights from a practical perspective. An epilogue summarizes the book and speculates on the role blockchain and its applications can play in the future. This book focusses on the bigger picture for blockchain, covering the concepts and technical considerations in the design of blockchain-based applications. The use of mathematical formulas is limited to where they are critical. This book is primarily intended for developers, software architects and chief information officers who need to understand the basic technology, tools and methodologies to build blockchain applications. It also provides students and researchers new to this field an introduction to this hot topic.
Chapter
This chapter introduces the three main techniques that exist to relate modeled and recorded behavior: rule checking, token replay, and alignments. For each technique, a gentle introduction is provided so that the reader can understand its main features, as well as the conformance feedback that can be obtained by its application. Running examples are used in the explanations to make the chapter very accessible to the reader.