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A Process Mining Approach for Supporting IoT Predictive Security
- 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.
- Subjects :
- Internet resources
Computer science
Distributed computing
0211 other engineering and technologies
Process mining
Pro- cess Mining
02 engineering and technology
Process Mining
Security Management
Order (exchange)
0202 electrical engineering, electronic engineering, information engineering
Data Mining
Security management
[INFO]Computer Science [cs]
Architecture
ComputingMilieux_MISCELLANEOUS
021110 strategic, defence & security studies
business.industry
020206 networking & telecommunications
Index Terms-Security Management
Internet-of-Things
Software deployment
Anomaly Detection
Anomaly detection
Internet of Things
business
Subjects
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