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        Obstructions in Security-Aware Business Processes

        Analysis, Detection, and Handling

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        Author(s)
        Holderer, Julius
        Collection
        DFG - German Research Foundation
        Language
        English
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        Abstract
        This Open Access book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software.
        URI
        https://library.oapen.org/handle/20.500.12657/57935
        Keywords
        IT-Security; Business Process Management; Security and Privacy; Process Security; Compliance; Process Automation; Process Modeling; Petri Net; Process Mining; Data Mining
        DOI
        10.1007/978-3-658-38154-7
        ISBN
        9783658381547, 9783658381547
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Wiesbaden, 2022
        Grantor
        • Deutsche Forschungsgemeinschaft (DFG)
        Imprint
        Springer Vieweg
        Classification
        Computer security
        Privacy and data protection
        Pages
        341
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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