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LIoPY: A legal compliant ontology to preserve privacy for the Internet of Things

Authors :
Chirine Ghedira-Guegan
Aïcha-Nabila Benharkat
Faiza Loukil
Khouloud Boukadi
Service Oriented Computing (SOC)
Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS)
Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-École Centrale de Lyon (ECL)
Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Université Lumière - Lyon 2 (UL2)
Multimedia, InfoRmation systems and Advanced Computing Laboratory (MIRACL)
Faculté des Sciences Economiques et de Gestion de Sfax (FSEG Sfax)
Université de Sfax - University of Sfax-Université de Sfax - University of Sfax
Source :
2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Jul 2018, Tokyo, Japan. ⟨10.1109/COMPSAC.2018.10322⟩, COMPSAC (2)
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

International audience; The Internet of Things (IoT) provides the opportunity to collect, process and analyze data. This opportunity helps to understand preferences and life patterns of individuals in order to offer them customized services. However, privacy has become a significant issue due to the personal nature of the knowledge derived from these data and the involved potential risks. Despite the increasing legislation pressure, few proposed solutions havedealt with the privacy requirements, such as consent and choice, purpose specification, and collection limitation. In this paper, we propose a privacy ontology in order to incorporate privacy legislation into privacy policies while considering several privacy requirements. Our proposed ontology aims both at making the smart devices more autonomous and able to infer data access rights and enforcing the privacy policy compliance atthe execution level. We implemented and evaluated our privacy ontology based on a healthcare scenario.

Details

Language :
English
Database :
OpenAIRE
Journal :
2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Jul 2018, Tokyo, Japan. ⟨10.1109/COMPSAC.2018.10322⟩, COMPSAC (2)
Accession number :
edsair.doi.dedup.....65ebdceb27e32fe8512383436df8572d
Full Text :
https://doi.org/10.1109/COMPSAC.2018.10322⟩