Trust Mining: Analyzing Trust in Collaborative Business Processes

Müller, Marcel; Ostern, Nadine; Koljada, Denis; Grunert, Kai; Rosemann, Michael; Küpper, Axel

doi:10.1109/access.2021.3075568

Cited by 8 publications

(3 citation statements)

References 43 publications

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“…Although it is unpredictable (Park and Shapira, 2017), a large part of this uncertainty is not caused by the internal problems of the software but by the external environments in which it is deployed. This is because, a part of the uncertainty can be exposed during the software testing phase or in the interaction with the external environment that may produce unexpected disturbances (Müller et al, 2021), timely fixes and remedies can eliminate this part of the uncertainty. In addition, modeling and predicting disruptions or impacts from unknown external environments can be difficult, such as the multi-vector attacks on the software supply chain.…”

Section: Knowledge-based Trust -Trust In Softwarementioning

confidence: 99%

A Systematic Literature Review on Trust in the Software Ecosystem

Hou¹,

Jansen²

2022

Preprint

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Background: The worldwide software ecosystem is a trust-rich part of the world. Throughout the software life cycle, software engineers, software end-users, and other stakeholders collaboratively place their trust in major hubs in the ecosystem, such as package managers, repository services, and software components. However, as our reliance on software grows, this trust is frequently violated by bad actors and crippling vulnerabilities in the software supply chain, endangering our livelihoods and the resilience of our society. Purpose: The purpose of this study is to define trust in the worldwide software ecosystem, that is, to determine what signifies a trustworthy system or actor. By improving our understanding of trust, we can create novel mechanisms for protecting the software ecosystem from vulnerabilities and attacks. Methods: We conduct a systematic literature review on the concept of trust in the worldwide software ecosystem. We acknowledge that trust is something between two actors in the software ecosystem, and we examine what role trust plays in the relationships between end-users and (1) software products, (2) package managers, (3) software producing organizations, and (4) software engineers. Results: Two major findings emerged from the systematic literature review. To begin, we provide a definition of trust in the software ecosystem, including a theoretical framework that decomposes and signifies a theoretical understanding of trust. Second, we provide a list of trust factors that can be used to assemble an overview of software trust. Conclusion: Trust is critical in the communication between actors in the worldwide software ecosystem, particularly regarding software selection and evaluation, and can affect the outcome either positively or negatively. According to the frequency

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Section: Knowledge-based Trust -Trust In Softwarementioning

confidence: 99%

A Systematic Literature Review on Trust in the Software Ecosystem

Hou¹,

Jansen²

2022

Preprint

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“…As discussed in [11], in collaborative processes where different organizations execute different parts of a shared process, the internal activities carried out by each organization are beyond the control of the other collaborators resulting in uncertainty regarding process execution. Whenever there is uncertainty in a process, there is a need for trust.…”

Section: Process Mining For Promoting Trustworthy Aimentioning

confidence: 99%

Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities

Pery¹,

Rafiei²,

Simon³

et al. 2021

Preprint

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The premise of this paper is that compliance with Trustworthy AI governance best practices and regulatory frameworks is an inherently fragmented process spanning across diverse organizational units, external stakeholders, and systems of record, resulting in process uncertainties and in compliance gaps that may expose organizations to reputational and regulatory risks. Moreover, there are complexities associated with meeting the specific dimensions of Trustworthy AI best practices such as data governance, conformance testing, quality assurance of AI model behaviors, transparency, accountability, and confidentiality requirements. These processes involve multiple steps, hand-offs, re-works, and human-in-the-loop oversight. In this paper, we demonstrate that process mining can provide a useful framework for gaining fact-based visibility to AI compliance process execution, surfacing compliance bottlenecks, and providing for an automated approach to analyze, remediate and monitor uncertainty in AI regulatory compliance processes.

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“…The business process is performed according to a set of complex rules that aim to integrate and synchronize the operation, such as transaction and management system, and support the ultimate goals of the process [1,2]. In a collaboration of multiple organizations, it is important to achieve an organic connection and integrity [3]. A collaborative business process improves the workflow among the related organizations, and it is important to set up a task model as well as analyze the mutual operation pattern in the collaboration [4].…”

Section: Introductionmentioning

confidence: 99%

A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

Jeon¹,

Kim²,

Shin³

et al. 2023

Computer Systems Science and Engineering

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The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment. However, while collaborative business expands the realm of businesses, it also causes various hazards in collaborative Interaction, such as data falsification, inconstancy, and misuse. To solve these issues, a blockchainbased collaborative business modeling approach was proposed and analyzed. However, the existing studies lack the blockchain risk problem-solving specification, and there is no verification technique to examine the process. Consequently, it is difficult to confirm the appropriateness of the approach. Thus, here, we propose and build a blockchain-based trust model to strengthen and verify the integrity and security of the collaborative business process; Integrity and security address the validity of collaborative interactions in terms of a trust, and we construct a blockchain pattern based on trust elements to meet the required the characteristics. Specifically, a trust model can be applied to the healthcare data-sharing process, and then the achievement of the trustbased safe data-sharing process can be proven. Our model can be used as a trust-building guidance tool or for integrity and security verification with the collaborative business process in a distributed environment with blockchain.

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Trust Mining: Analyzing Trust in Collaborative Business Processes

Cited by 8 publications

References 43 publications

A Systematic Literature Review on Trust in the Software Ecosystem

A Systematic Literature Review on Trust in the Software Ecosystem

Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities

A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

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