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Modelling of Railway Signalling System Requirements by Controlled Natural Languages: A Case Study

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From Software Engineering to Formal Methods and Tools, and Back

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11865))

Abstract

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.

Lenzini is supported by Luxembourg National Research Fund (FNR) CORE project C16/IS/11333956 “DAPRECO: DAta Protection REgulation COmpliance”; Petrocchi is supported by the TOFFEe Integrated Activity Project funded by IMT Scuola Alti Studi Lucca.

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Notes

  1. 1.

    www.roll2rail.eu.

  2. 2.

    www.in2rail.eu.

  3. 3.

    www.shift2rail.eu.

  4. 4.

    Not that it matters in the argument we are here developing, but one of the authors recalls to have worked in his early PhD to the validation of a safety-critical hardware system for the management of medium-large railway networks against the occurrence of Byzantine faults [18].

  5. 5.

    www.cyrail.eu.

  6. 6.

    https://www.enisa.europa.eu/events/first-transport-cyber-security-conference/.

  7. 7.

    www.era.europa.eu/activities/technical-specifications-interoperability_en.

  8. 8.

    The integration of the NL2CNL Translator is under development.

  9. 9.

    The description of the L3 signalling system is kindly provided by the authors of [3].

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Acknowledgement

This work has been written for the Festschrift in honor of Stefania Gnesi, head of the Formal Methods & Tools group of the Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” (ISTI) of the National Council of Research (CNR), in Pisa, Italy. Both authors wish to express their professional and personal gratitude to Stefania for the time spent together at the CNR in Pisa and for years of fruitful collaboration. Stefania has been our mentor but she is also a friend. Rephrasing what we took from a comic strip about Livorno, the seaside town where she lives, we could affectionately say: “È una livornese, una donna forte con un cuore di madre”.

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Authors and Affiliations

  1. Interdisciplinary Center for Security Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Luxembourg

    Gabriele Lenzini

  2. Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche (IIT-CNR), Pisa, Italy

    Marinella Petrocchi

  3. IMT Scuola Alti Studi Lucca, Lucca, Italy

    Marinella Petrocchi

Authors
  1. Gabriele Lenzini
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Correspondence to Gabriele Lenzini .

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Editors and Affiliations

  1. Consiglio Nazionale delle Ricerche, Pisa, Italy

    Maurice H. ter Beek

  2. Università degli Studi di Firenze, Florence, Italy

    Alessandro Fantechi

  3. Università di Pisa, Pisa, Italy

    Laura Semini

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Lenzini, G., Petrocchi, M. (2019). Modelling of Railway Signalling System Requirements by Controlled Natural Languages: A Case Study. In: ter Beek, M., Fantechi, A., Semini, L. (eds) From Software Engineering to Formal Methods and Tools, and Back. Lecture Notes in Computer Science(), vol 11865. Springer, Cham. https://doi.org/10.1007/978-3-030-30985-5_29

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  • DOI: https://doi.org/10.1007/978-3-030-30985-5_29

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