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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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Keywords :
System Modelling; Railway Systems; CNL4DSA
Abstract :
[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.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Applied Security and Information Assurance Group (APSIA)
Disciplines :
Computer science
Author, co-author :
Lenzini, Gabriele ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Petrocchi, Marinella
External co-authors :
yes
Language :
English
Title :
Modelling of Railways Signalling System Requirements by Controlled Natural Languages: A Case Study
Publication date :
09 October 2019
Main work title :
From Software Engineering to Formal Methods and Tools, and Back
Publisher :
Springer, Cham
ISBN/EAN :
978-3-030-30984-8
Collection name :
Lecture Notes In Computer Science, volume 11865
Pages :
502-518
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR11333956 - Data Protection Regulation Compliance, 2016 (01/02/2017-30/06/2019) - Gabriele Lenzini
Name of the research project :
DAPRECO
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
since 09 October 2019

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