A Process Mining Approach for Supporting IoT Predictive Security - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year :

A Process Mining Approach for Supporting IoT Predictive Security


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.
Fichier principal
Vignette du fichier
noms.pdf (1.62 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02402986 , version 1 (04-06-2020)


  • HAL Id : hal-02402986 , version 1


Adrien Hemmer, Remi Badonnel, Isabelle Chrisment. A Process Mining Approach for Supporting IoT Predictive Security. NOMS 2020 - IEEE/IFIP Network Operations and Management Symposium, Apr 2020, Budapest, Hungary. ⟨hal-02402986⟩
307 View
224 Download


Gmail Facebook Twitter LinkedIn More