Mathieu BRILAND : "Address false data injection attacks in IoT systems using a dedicated language in an industrial context"

PhD works of  Mathieu BRILAND : "Address false data injection attacks in IoT systems using a dedicated language in an industrial context"

Abstract : The Internet of Things (IoT) is nowadays ubiquitous in all spheres of life. Its applications can be found in many fields, such as smart cities, industry, health, home automation, etc. The rapid explosion of the Internet of Things has seen the emergence of numerous security issues, notably due to the great heterogeneity of "things" and their protocols, as well as the lack of dedicated standards. This thesis focuses on a specific security problem existing within the IoT, False Data Injection Attacks (FDIA). Indeed, the services provided by the IoT rely on the use of data retrieved by numerous sensors. One of the many attack vectors is then the data transiting within the devices. To allow the description and the implementation of these attacks, we propose an approach using a Domain-Specific Language allowing to model FDIA, to test the resilience of IoT systems and to help the development of detection tools for such attacks. This work took place within the company Flowbird, the world leader in parking solutions, which allowed us to use its devices to develop our approach.

Jury Composition :

M. Fabrice BOUQUET Professeur des universités Université Bourgogne Franche-Comté PhD Director
M. Yves LE TRAON Professeur des universités Université du Luxembourg Reporter
M. Ioannis PARISSIS Professeur des universités Université de Grenoble-Alpes Reporter
M. Yohann GUIOT Flowbird Reviewer
M. Bruno LEGEARD Professeur des universités Université Bourgogne Franche-Comté Reviewer

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