Our Publications
Here you find our publications.
2020
Bourget, Edwin; Cuppens, Frédéric; Cuppens-Boulahia, Nora
PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis Inproceedings
In: Proceedings of the 6th ACM on Cyber-Physical System Security Workshop, pp. 30–41, ACM, New York, NY, USA, 2020, ISBN: 9781450376082.
Abstract | Links | BibTeX | Tags: countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security
@inproceedings{Bourget2020b,
title = {PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis},
author = {Edwin Bourget and Fr\'{e}d\'{e}ric Cuppens and Nora Cuppens-Boulahia},
url = {https://dl.acm.org/doi/10.1145/3384941.3409590},
doi = {10.1145/3384941.3409590},
isbn = {9781450376082},
year = {2020},
date = {2020-10-01},
booktitle = {Proceedings of the 6th ACM on Cyber-Physical System Security Workshop},
pages = {30--41},
publisher = {ACM},
address = {New York, NY, USA},
abstract = {The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.},
keywords = {countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security},
pubstate = {published},
tppubtype = {inproceedings}
}
The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.
Bourget, Edwin; Cuppens, Frédéric; Cuppens-Boulahia, Nora
PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis Journal Article
In: CPSS 2020 - Proceedings of the 6th ACM Cyber-Physical System Security Workshop, Co-located with AsiaCCS 2020, pp. 30–41, 2020, ISBN: 9781450376082.
Abstract | Links | BibTeX | Tags: countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security
@article{Bourget2020a,
title = {PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis},
author = {Edwin Bourget and Fr\'{e}d\'{e}ric Cuppens and Nora Cuppens-Boulahia},
doi = {10.1145/3384941.3409590},
isbn = {9781450376082},
year = {2020},
date = {2020-01-01},
journal = {CPSS 2020 - Proceedings of the 6th ACM Cyber-Physical System Security Workshop, Co-located with AsiaCCS 2020},
pages = {30--41},
abstract = {The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.},
keywords = {countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security},
pubstate = {published},
tppubtype = {article}
}
The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.
Bourget, Edwin; Cuppens, Frédéric; Cuppens-Boulahia, Nora
PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis Journal Article
In: CPSS 2020 - Proceedings of the 6th ACM Cyber-Physical System Security Workshop, Co-located with AsiaCCS 2020, pp. 30–41, 2020, ISBN: 9781450376082.
Abstract | Links | BibTeX | Tags: countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security
@article{Bourget2020,
title = {PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis},
author = {Edwin Bourget and Fr\'{e}d\'{e}ric Cuppens and Nora Cuppens-Boulahia},
doi = {10.1145/3384941.3409590},
isbn = {9781450376082},
year = {2020},
date = {2020-01-01},
journal = {CPSS 2020 - Proceedings of the 6th ACM Cyber-Physical System Security Workshop, Co-located with AsiaCCS 2020},
pages = {30--41},
abstract = {The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.},
keywords = {countermeasures, Cyber-Physical Systems, diagnosis, event model, industrial systems, safety, Security},
pubstate = {published},
tppubtype = {article}
}
The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.
