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Modelling of Railways Signalling System Requirements by Controlled Natural Languages: A Case Study
LENZINI, Gabriele; Petrocchi, Marinella
2019In From Software Engineering to Formal Methods and Tools, and Back
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Mots-clés :
System Modelling; Railway Systems; CNL4DSA
Résumé :
[en] The railway sector has been a source of inspiration for generations of researchers challenged to develop models and tools to analyze safety and reliability. Threats were coming mainly from within, due to occasionally faults in hardware components. With the advent of smart trains, the railway industry is venturing into cybersecurity and the railway sector will become more and more compelled to protect assets from threats against information & communication technology. We discuss this revolution at large, while speculating that instruments developed for security requirements engineering can then come in support of in the railway sector. And we explore the use of one of them: the Controlled Natural Language for Data Sharing Agreement (CNL4DSA). We use it to formalize a few exemplifying signal management system requirements. Since CNL4DSA enables the automatic generation of enforceable access control policies, our exercise is preparatory to implementing the security-by design principle in railway signalling management engineering.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Applied Security and Information Assurance Group (APSIA)
Disciplines :
Sciences informatiques
Auteur, co-auteur :
LENZINI, Gabriele  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Petrocchi, Marinella
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Modelling of Railways Signalling System Requirements by Controlled Natural Languages: A Case Study
Date de publication/diffusion :
09 octobre 2019
Titre de l'ouvrage principal :
From Software Engineering to Formal Methods and Tools, and Back
Maison d'édition :
Springer, Cham
ISBN/EAN :
978-3-030-30984-8
Collection et n° de collection :
Lecture Notes In Computer Science, volume 11865
Pagination :
502-518
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
Projet FnR :
FNR11333956 - Data Protection Regulation Compliance, 2016 (01/02/2017-30/06/2019) - Gabriele Lenzini
Intitulé du projet de recherche :
DAPRECO
Organisme subsidiant :
FNR - Fonds National de la Recherche
Disponible sur ORBilu :
depuis le 09 octobre 2019

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