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Correct and Efficient Policy Monitoring, a Retrospective

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Automated Technology for Verification and Analysis (ATVA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14215))

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Abstract

The MonPoly project started over a decade ago to build effective tools for monitoring trace properties, including functional correctness, security, and compliance policies. The original MonPoly tool supported monitoring specifications given in metric first-order temporal logic, an expressive specification language. It handled both the online case, where system events are monitored as they occur, and the offline case, monitoring logs. Our tool has evolved over time into a family of tools and supporting infrastructure to make monitoring both scalable and suitable for high assurance applications. We survey this evolution which includes: (1) developing more expressive monitors, e.g., adding aggregation operators, regular expressions, and limited forms of recursion; (2) delimiting efficiently monitorable fragments and designing new monitoring algorithms for them; (3) supporting parallel and distributed monitoring; (4) using theorem proving to verify monitoring algorithms and explore extensions; and (5) carrying out ambitious case studies.

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Notes

  1. 1.

    Although not every safety property expressible in MFOTL has this form [47].

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Acknowledgments

This paper has four authors, but it reports on a decade of collaboration with numerous other researchers. We would like to explicitly name some of them here. First and foremost, we thank Felix Klaedtke, Martin Raszyk, and Eugen Zălinescu. Felix and Eugen were key contributors during the inception of MonPoly. Martin arrived later but left his mark through his work on Hydra, Vydra, MFOTL2RANF, and VeriMon.

We also thank the past and present monitoring aficionados from our groups at ETH Zürich and the University of Copenhagen: Bhargav Bhatt, Rafael Castro G. Silva, Matús Harvan, François Hublet, Jonathan Julián Huerta y Munive, Leonardo Lima, Srđan Marinović, Samuel Müller, Lennard Reese. In addition, we are grateful to those B.Sc. and M.Sc. students who contributed to our journey: Berkay Aydogdu, Marc Bolliger, Frederik Brix, Thibault Dardinier, Christian Fania, Artur Gigon Almada e Melo, Matthieu Gras, Emma Pind Hansen, Nico Hauser, Lukas Heimes, Andrei Herasimau, Hróbjartur Höskuldsson, Valeria Jannelli, Nicolas Kaletsch, Jeniffer Lima Graf, Emanuele Marsicano, Galina Peycheva, Sarah Plocher, Jonathan Rappl, Pascal Schärli, Dawit Legesse Tirore, Adrian Wortmann, Simon Yuan, Stefan Zemljic, Sheila Zingg, and Remo Zumsteg. We would also like to thank our external collaborators from the past and present: Emma Arfelt, Daniel Bristot de Oliveira, Germano Caronni, Søren Debois, Daniel Stefan Dietiker, Sarah Ereth, Yliès Falcone, Heiko Mantel, Birgit Pfitzmann, Yvonne-Anne Pignolet, Giles Reger, Arshavir Ter-Gabrielyan, as well as the participants of the ARVI COST Action and many (mostly) anonymous reviewers.

Finally, we acknowledge the generous external funding we have received for research on monitoring from the Swiss National Science Foundation (grant 167162 “Big Data Monitoring” and grant 204796 “Model-driven Security & Privacy”), the US Air Force Research Laborarory (grant FA9550-17-1-0306 “Monitoring at Any Cost”), and the Novo Nordisk Foundation (start package grant NNF20OC0063462).

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Authors and Affiliations

  1. Institute of Information Security, Department of Computer Science, ETH Zurich, Zürich, Switzerland

    David Basin, Srđan Krstić & Joshua Schneider

  2. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Dmitriy Traytel

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  1. David Basin
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  2. Srđan Krstić
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  3. Joshua Schneider
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  4. Dmitriy Traytel
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Correspondence to David Basin .

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Editors and Affiliations

  1. Université Sorbonne Paris Nord, Villetaneuse, France

    Étienne André

  2. Singapore Management University, Singapore, Singapore

    Jun Sun

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Basin, D., Krstić, S., Schneider, J., Traytel, D. (2023). Correct and Efficient Policy Monitoring, a Retrospective. In: André, É., Sun, J. (eds) Automated Technology for Verification and Analysis. ATVA 2023. Lecture Notes in Computer Science, vol 14215. Springer, Cham. https://doi.org/10.1007/978-3-031-45329-8_1

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