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Reference Architecture of Cybersecurity Digital Twin 2nd

Reference Architecture of Cybersecurity Digital Twin

引用

28th International Conference on Enterprise Design Operations and Computing

作者： Itapelto, Taru Elhajj, Mohammed van Sinderen, Marten Iacob, Maria Univ Twente Semant Cybersecur & Serv EEMCS SCS POB 217 NL-7500 AE Enschede Netherlands Univ Twente Sect Ind Engn & Business Informat Syst BMS HBE IE POB 217 NL-7500 AE Enschede Netherlands

ISBN: (纸本)9783031790584;9783031790591

The transformation of previously isolated Critical Infrastructures (CIs) into intricate Systems-of-Systems has rendered them vulnerable to various threats. CIs are characterized by long life cycles and high availability requirements, which pose significant challenges in maintaining cybersecurity throughout their operational life cycle. Existing testing methodologies prove inadequate and may compromise the CI's operational continuity. This paper proposes to shift testing activities to a Digital Twin (DT) connected to the CI. The DT provides a digital counterpart of the real system, enabling cost-effective testing without compromising operational integrity. For this approach, we present an enterprise architecture called the cybersecurity DT reference architecture. Through a camera surveillance system use case, we demonstrate the feasibility of this reference architecture, focusing on what-if testing using DT-enabled attack simulations. We show how to enhance decision-making when evaluating system configurations and how to deploy optimized configurations to the real system.

关键词： Digital Twin Critical Infrastructure cybersecurity Enterprise Architecture DT

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Governance Practices for Open Source Foundations in the Healthcare Sector 1

引用

15th International Conference on Software business-ICSOB-Annual

作者： Yavuz, Elxin Yenisen Shrivastava, Akshat Riehle, Dirk Putz, Florian Friedrich Alexander Univ Erlangen Nurnberg Erlangen Germany Univ Klink Erlangen Nurnberg Erlangen Germany

ISBN: (数字)9783031858499

ISBN: (纸本)9783031858482;9783031858499

Open source (OS) foundations are non-profit organizations that support open-source software development projects. OS foundations can be categorized based on their membership and governance structures. This study focuses on vendor-led and user-led OS foundations operating in the healthcare sector. The study has two objectives. The first objective is to explore the similarities and differences of vendor-led and user-led OS foundations. The second objective is to explore and define governance practices applied in these foundations to achieve success. To address these objectives, we performed multiple-case study research, with the openEHR Foundation and the RACOON consortium as our cases. We performed interviews with key stakeholders and applied thematic analysis to derive the results. We present differences and similarities of these foundations with respect to membership and organizational structure. We also present members' motivation to engage with these foundations. Furthermore, we identify and explain 32 governance practices applied in nine contexts related to OS foundations in the healthcare sector.

关键词： open source foundation governance practices best practices openEHR RACOON

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Enhancing API Labelling with BERT and GPT: An Exploratory Study 2nd

Enhancing API Labelling with BERT and GPT: An Exploratory St...

引用

28th International Conference on Enterprise Design Operations and Computing

作者： Morais, Gabriel Lemelin, Edwin Adda, Mehdi Bork, Dominik Univ Quebec Rimouski Levis PQ G6V 1L8 Canada Univ Laval Quebec City PQ G1V 0A6 Canada TU Wien Business Informat Grp Vienna Austria

ISBN: (纸本)9783031790584;9783031790591

Application Programming Interfaces (APIs) enable interaction, integration, and interoperability among applications and services, contributing to their adoption and proliferation. However, discovering APIs has relied on manual, time-consuming, costly processes that jeopardize their reuse potential and accentuate the need for effective API retrieval mechanisms. Leveraging the OpenAPI Specification as a basis, this paper presents an exploratory study that combines BERT and GPT machine learning models to propose a novel API classifier. Our investigation explored the zero-shot learning capabilities of GPT-4 and GPT-3.5 using relevant terms extracted from API descriptions using BERT. The evaluation of our approach on two datasets comprising 940 API descriptions sourced from public repositories yielded an F1-score of 100% in the small dataset (17 APIs) and 39.1% in the large dataset (923 APIs). These results surpass state-of-the-art on the small dataset with an impressive 29-point improvement. The large dataset showed GPT can suggest labels not in the provided list. Manual analysis revealed that GPT's suggested labels fit the API intent better in 18 out of 20 cases, highlighting its potential for unknown classes and mismatch detection. This emphasizes the need to improve dataset quality and availability for API research. Our findings show the potential of automated API retrieval and open avenues for future research.

关键词： API classification OpenAPI Specification GPT BERT

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Transforming Object-Centric Event Logs to Temporal Event Knowledge Graphs 22nd

Transforming Object-Centric Event Logs to Temporal Event Kno...

引用

22nd International Conference on business Process Management (BPM)

作者： Khayatbashi, Shahrzad Hartig, Olaf Jalali, Amin Linkoping Univ Linkoping Sweden Stockholm Univ Stockholm Sweden

ISBN: (纸本)9783031786655;9783031786662

Event logs play a fundamental role in enabling data-driven business process analysis. Traditionally, these logs track events related to a single object, known as the case, limiting the scope of analysis. Recent advancements, such as Object-Centric Event Log (OCEL) and Event Knowledge Graph (EKG), capture better how events relate to multiple objects. However, attributes of objects can change over time, which was not initially considered in OCEL or EKG. While OCEL 2.0 has addressed some of these limitations, there remains a research gap concerning how attribute changes should be accommodated in EKG and how OCEL 2.0 logs can be transformed into EKG. This paper fills this gap by introducing Temporal Event Knowledge Graph (tEKG) and defining an algorithm to convert an OCEL 2.0 log to a tEKG.

关键词： Event Knowledge Graphs Object-Centric Event Data Object-Centric Process Mining

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Revision of a Smart Factory Software Architecture from Monolith to Microservices 2nd

Revision of a Smart Factory Software Architecture from Monol...

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28th International Conference on Enterprise Design Operations and Computing

作者： Seiger, Ronny Malburg, Lukas Univ St Gallen Inst Comp Sci CH-9000 St Gallen Switzerland Univ Trier Artificial Intelligence & Intelligent Informat Sy D-54296 Trier Germany Branch Univ Trier German Res Ctr Artificial Intelligence DFKI Behringstr 21 D-54296 Trier Germany

ISBN: (纸本)9783031790584;9783031790591

Software architecture plays an important role in the development of modern, complex software systems as it influences a system's quality attributes and ability to grow with future demand. Designing the software architecture of cyber-physical systems (CPS) becomes even more challenging due to their capability of directly influencing the physical world and thus introducing new non-functional requirements related to fault-tolerance, safety, and resource scarcity. Existing research focuses on systems engineering to achieve the vertical integration of CPS with an organization's information systems and processes, but not on software architecture to horizontally extend existing systems with new CPS. In this report we describe the process of revising an existing monolithic software architecture for a smart factory towards a microservices-based architecture to meet these new requirements and prepare the factory to be extended with new CPS. For the revision of the existing architecture, we provide an analysis of its code base before and after changes, a description of the refactoring process, and discuss relevant new non-functional requirements and architecture options. We elaborate on the architectural decisions favoring microservices and analyze the new architecture regarding improved quality attributes to evaluate the system.

关键词： Cyber-physical Systems Software Architecture Internet of Things Microservices Industry 4.0

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Optimizing for Sustainability: Product Ops and Software Waste Reduction 1

引用

15th International Conference on Software business-ICSOB-Annual

作者： Moroz, Bogdan Saltan, Andrey Hyrynsalmi, Sami LUT Univ Lahti Finland

ISBN: (数字)9783031858499

ISBN: (纸本)9783031858482;9783031858499

In today's competitive software-intensive industries, the pursuit of sustainability is increasingly recognized as one of the important drivers of long-term performance. While lean methodologies focusing on waste reduction are widely adopted across various domains, the software-intensive industries face unique challenges when applying these principles. The emergence of Product Operations (Product Ops) in product-led companies presents new opportunities for improving operational efficiency and reducing waste within software development processes. This paper investigates the role of Product Ops in addressing different types of software development waste by mapping the responsibilities and impacts of Product Ops to these types of waste. The results indicate that Product Ops may help reduce multiple forms of waste, contributing to the sustainability of software businesses. This exploratory study lays the foundation for further research examining the impact of Product Ops on the sustainability of software companies.

关键词： Product Operations Product Ops Product Management Sustainability Software Engineering Software business Lean Waste Management

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Knowledge Graphs: A Key Technology for Explainable Knowledge-Aware Process Automation? 22nd

Knowledge Graphs: A Key Technology for Explainable Knowledge...

引用

22nd International Conference on business Process Management (BPM)

作者： Bein, Leon Pufahl, Luise Tech Univ Munich Sch Computat Informat & Technol Heilbronn Germany

ISBN: (纸本)9783031786655;9783031786662

Process automation is a key subfield of business process management. Recent advances in AI research promise to yield a new type of intelligent process automation that can support high-variability, flexible, knowledge-intensive processes previously hard to enhance with process automation. However, primarily proposed, subsymbolic deep learning approaches fail to reliably consider the complex knowledge inherent to these processes and provide adequate explanations for their decisions. Neuro-symbolic reasoning approaches based on knowledge graphs promise to address these challenges by allowing to holistically encode complex domain knowledge and to perform explainable reasoning thereupon. In this vision paper, we investigate the potential of knowledge graphs for intelligent process automation. Using tangible examples, we show how they can be used to enable explainable, knowledge-aware process automation, integrating a wide range of process knowledge. We show that such knowledge-aware process automation can contribute to addressing two current challenges of the BPM community: the automation of knowledge-intensive processes and the design of AI-augmented business process management systems. Finally, we discuss avenues for future research.

关键词： business Process Automation Knowledge Graphs Knowledge-intensive Processes Neuro-symbolic AI

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Leveraging Generative Vision Models for Extracting Process Models from Documents 22nd

Leveraging Generative Vision Models for Extracting Process M...

引用

22nd International Conference on business Process Management (BPM)

作者： Voelter, Marvin Hadian, Raheleh Kampik, Timotheus Breitmayer, Marius Reichert, Manfred SAP Berlin Germany Ulm Univ Ulm Germany

ISBN: (纸本)9783031786655;9783031786662

This paper investigates the vision capabilities of multimodal Generative Pre-trained Transformers (GPTs) to auto-generate structured process models from diagram- and text-based documents. We introduce a dataset of 123 process models and corresponding documentation, emphasizing real-world element distributions. Using evaluation metrics for process model similarity, this enables ground truth-based assessment of process model generation. We evaluate commercial GPT capabilities with zero-, one-, and few-shot prompting strategies. Our results indicate that generative vision models can be useful tools for semi-automated process modeling based on multimodal documents. More importantly, the dataset and evaluation metrics as well as the open-source evaluation code provide a structured framework for continued systematic evaluations moving forward.

关键词： Generative Vision Models Multimodal Large Language Models Document Analysis business Process Management

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Enhancement of Low-Level Event Abstraction with Large Language Models (LLMs) 22nd

Enhancement of Low-Level Event Abstraction with Large Langua...

引用

22nd International Conference on business Process Management (BPM)

作者： Brzychczy, Edyta Kluza, Krzysztof Szala, Leszek AGH Univ Krakow Mickiewicza Ave 30 PL-30059 Krakow Poland Univ Chem & Technol Dept Math Informat & Cybernet Fac Chem Engn Tech 5 Prague 16628 6 Czech Republic

ISBN: (纸本)9783031786655;9783031786662

Event abstraction enables transformation of low level events into higher level events making process mining (PM) on sensor data available. There are many approaches to event abstraction described in literature, however the main approaches include supervised or unsupervised techniques. We address the challenge of transforming low-level sensor data into high-level activities required for effective process mining, a task traditionally reliant on domain experts. By leveraging LLMs to automate the labelling process of sensor data clusters, we bridge the gap between raw data and process models. Motivated by a mining industry use case, we validated the effectiveness of LLMs in accurately labelling operational phases. Our LLM-generated labelling rules demonstrated high accuracy and interpretability, simplifying the understanding for domain experts. Additionally, we compared our LLM-based approach with a Decision Tree Classifier, highlighting the advantages of LLMs in generating simpler, more understandable labelling functions. Our work underscores the potential of advanced AI techniques to enhance the efficiency and accuracy of PM, contributing to the Industry 4.0 initiative.

关键词： Event abstraction Sensor data LLMs Process mining

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Check My Flow: Distributed Conformance Checking at the Source 22nd

Check My Flow: Distributed Conformance Checking at the Sourc...

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22nd International Conference on business Process Management (BPM)

作者： Andersen, Julia Rathje, Patrick Landsiedel, Olaf Univ Kiel D-24118 Kiel Germany

ISBN: (纸本)9783031786655;9783031786662

IoT networks in, for example, smart manufacturing, smart homes, and smart health demand process mining beyond traditional event logs. However, conventional process discovery and conformance checking algorithms expect data to be collected at a central location for mining. As a result, they struggle to handle the vast amounts of data generated by IoT networks, which often leads to privacy concerns. To address these challenges, this paper introduces Distributed Conformance Checking (DisCC). DisCC leverages a footprint-fitness method to perform distributed online conformance checks directly at the data source where an event is sensed, ensuring scalable conformance checking and enabling privacy by only sharing aggregated event data with a central entity. Our evaluation of DisCC demonstrates its effectiveness in accurately performing conformance checks at the event, trace, and log levels. We experimentally show the correctness of DisCC and how quickly its interim results converge to the correct fitness value. The system supports real-time alerts for non-conforming events and traces, detects concept drifts and temporary fitness losses through a sliding window implementation, and offers a scalable, privacy-enabling solution for process monitoring in IoT networks.

关键词： Online Conformance Checking Distributed Process Mining Event Data Stream Scalability

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