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A Process Mining Approach for Supporting IoT Predictive Security

Authors :
Isabelle Chrisment
Rémi Badonnel
Adrien Hemmer
Resilience and Elasticity for Security and ScalabiliTy of dynamic networked systems (RESIST)
Inria Nancy - Grand Est
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Networks, Systems and Services (LORIA - NSS)
Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
TELECOM Nancy
Université de Lorraine (UL)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
European Project: 779899,H2020,SecureIoT(2018)
Source :
NOMS 2020-IEEE/IFIP Network Operations and Management Symposium, NOMS 2020-IEEE/IFIP Network Operations and Management Symposium, Apr 2020, Budapest, Hungary, ieee-noms.org, NOMS, NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

Abstract

International audience; The growing interest for the Internet-of-Things (IoT) is supported by the large-scale deployment of sensors and connected objects. These ones are integrated with other Internet resources in order to elaborate more complex and value-added systems and applications. While important efforts have been done for their protection, security management is a major challenge for these systems, due to their complexity, their heterogeneity and the limited resources of their devices. In this paper we introduce a process mining approach for detecting misbehaviors in such systems. It permits to characterize the behavioral models of IoT-based systems and to detect potential attacks, even in the case of heterogenous protocols and platforms. We then describe and formalize its underlying architecture and components, and detail a proof-of-concept prototype. Finally, we evaluate the performance of this solution through extensive experiments based on real industrial datasets.

Details

Language :
English
ISBN :
978-1-72814-973-8
ISBNs :
9781728149738
Database :
OpenAIRE
Journal :
NOMS 2020-IEEE/IFIP Network Operations and Management Symposium, NOMS 2020-IEEE/IFIP Network Operations and Management Symposium, Apr 2020, Budapest, Hungary, ieee-noms.org, NOMS, NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium
Accession number :
edsair.doi.dedup.....577ee6f96f8c90495bb5f9c4d545e337