@inproceedings{54145b28c4fa4f6682fe6b612fc26117,
title = "On the Semantics of Risk Propagation",
abstract = "Risk propagation encompasses a plethora of techniques for analyzing how risk “spreads” in a given system. Albeit commonly used in technical literature, the very notion of risk propagation turns out to be a conceptually imprecise and overloaded one. This might also explain the multitude of modeling solutions that have been proposed in the literature. Having a clear understanding of what exactly risk is, how it be quantified, and in what sense it can be propagated is fundamental for devising high-quality risk assessment and decision-making solutions. In this paper, we exploit a previous well-established work about the nature of risk and related notions with the goal of providing a proper interpretation of the different notions of risk propagation, as well as revealing and harmonizing the alternative semantics for the links used in common risk propagation graphs. Finally, we discuss how these results can be leveraged in practice to model risk propagation scenarios.",
keywords = "2023 OA procedure",
author = "Mattia Fumagalli and Gal Engelberg and {Prince Sales}, Tiago and {Da Silva Oliveira}, {{\'I}talo Jos{\'e}} and Dan Klein and Pnina Soffer and Riccardo Baratella and Giancarlo Guizzardi",
note = "Funding Information: BeCoDigital]. Financial support was also received from the European Regional Development Fund (ERDF) for the Wal-e-Cities project with award number [ETR121200003138] and from the Research Public Service of Wallonia (SPW Recherche) for the project ARIAC by DIGITALWALLONIA4AI with award number [2010235]. Funding Information: Acknowledgement. This research was supported by ERDF “CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence” (No. CZ.02.1.01/0.0/0.0/16_019/0000822). It was also co-founded by the European Union under Grant Agreement No. 101087529. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Funding Information: Acknowledgements. This research is supported by the Estonian Research Council (PRG1226) and the European Research Council (PIX Project). Funding Information: Unit 2023-2027 (CEX2021-001201-M) funded by MCIN/AEI /10.13039/501100011033, and the RCIS community for their valuable insights that helped develop this work. Funding Information: Acknowledgements. This work has been developed under the project Digital Knowledge Graph – Adaptable Analytics API with the financial support of Accenture LTD, the Generalitat Valenciana through the CoMoDiD project (CIPROM/2021/023), the Spanish State Research Agency through the DELFOS (PDC2021-121243-I00) and SREC (PID2021-123824OB-I00) projects, MICIN/AEI/10.13039/501 100011033 and co-financed with ERDF and the European Union Next Generation EU/PRTR. Funding Information: and H2020 Programmes under grant agreements 101070455 (DYNABIC), 101095634 (ENTRUST) and 101020416 (ERATOSTHENES), and the Research Council of Norway{\textquoteright}s BIA-IPN programme under grant agreement 309700 (FLEET). Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th International Conference on Research Challenges in Information Science, RCIS 2023, RCIS 2023 ; Conference date: 23-05-2023 Through 26-08-2023",
year = "2023",
month = may,
day = "23",
doi = "10.1007/978-3-031-33080-3_5",
language = "English",
isbn = "978-3-031-33079-7",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer",
pages = "69--86",
editor = "Selmin Nurcan and Opdahl, {Andreas L.} and Haralambos Mouratidis and Aggeliki Tsohou",
booktitle = "Research Challenges in Information Science: Information Science and the Connected World",
url = "https://www.rcis-conf.com/rcis2023/",
}