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Obstructions in Security-Aware Business Processes : Analysis, Detection, and Handling / by Julius Holderer

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Wiesbaden : Springer Fachmedien Wiesbaden, 2022Publisher: Wiesbaden : Imprint: Springer Vieweg, 2022Edition: 1st ed. 2022Description: 1 Online-Ressource(XXI, 341 p. 118 illus., 96 illus. in color.)ISBN:
  • 9783658381547
Subject(s): Additional physical formats: 9783658381530 | 9783658381554 | Erscheint auch als: 9783658381530 Druck-Ausgabe | Erscheint auch als: 9783658381554 Druck-AusgabeDOI: DOI: 10.1007/978-3-658-38154-7Online resources: Summary: Why the Automation of Regulation Can Obstruct Business Processes -- Security-Related Obstructability in Process-Aware Information Systems -- Obstruction Modeling -- OLive-M: A SecANet Use Case for Model-Based Obstruction Solving -- OLive-L: SecANet Use Case for Log-Based Obstruction Solving -- Towards Intelligent Security- and Process-Aware Information Systems -- Bibliography.Summary: 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. About the author Julius Holderer is a researcher in the area of security and compliance in business processes at the Faculty of Engineering of the University of Freiburg (Germany). He is interested in information, IT, and cyber security, as well as policy and process modeling, process automation and mining.PPN: PPN: 1811676618Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SOB
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