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Soutenance de doctorat de Jaweher Zouari

Soutenance de thèse de doctorat le  09/12/2019 à 09H00 à l'amphi Ibn Khaldoun de Sup'Com.

Intitulé : Privacy-Preserving Identity Management in the Internet of Things

Présentée par :  Jaweher Zouari



M. Hichem BESBES

Professeur, SUP'COM, Université de Carthage, Tunisie





M. Farid Nait-Abdessalem

Professeur à Université Paris Descartes


M. Rhouma Rhouma

Maître de conférences à ESEN



M. Sadok El Asmi

Professeur, SUP’COM, Université de Carthage, Tunisie




Directeur de Thèse :

M. Mohamed Hamdi

Maître de conférences, SUP'COM, Université de Carthage, Tunisie


Internet of Things (IoT) technology has transitioned from a luxury feature to a baseline aspect of our lives. IoT devices are instantly collecting, processing and analyzing user data. Most of these devices are connected to an anchor device such as a smartphone. Hacking one of these  IoT devices often gives access to every sensitive data hosted in the anchor device, and allows performing more sophisticated attacks on behalf of the user. Therefore, bolstering Identity  Management (IDM) and privacy-preservation in the IoT is of critical importance. This thesis first investigates IDM requirements in IoT and proposes novel solutions to tackle them.The first axis of this work focuses on user authentication to the anchor device. Due to the limitations of password-based and cryptographic-based authentication, the use of biometrics can be potentially seen as a viable approach. For instance, we propose a key binding scheme that binds a password to a biometric template to perform a two-factor authentication. As  privacy is at stake when dealing with biometrics, we focus on the protection of the privacy of the biometric template, namely the fingerprint, by granting irreversibility and unlinkability.  We also investigate the robustness of the proposed solution to alignment problems in order to assess the effects of distortions.The second axis of this thesis aims at providing an end-to-end secure transmission channel between the device layer and the upper layers, while ensuring data privacy during the underlying pre-processing steps . We combine fully additive encryption with fully additive secret sharing to fulfill the required properties such as confidentiality and compromise resiliency. Thorough security analysis and performance evaluation show a viable tradeoff between security and efficiency for our scheme. A sample of the aforementioned scheme is applied to a health telemetering usecase where we propose a privacy-preserving scheme for the transmission and pre-processing of pedobarometry sensory data without breaking the privacy of the health record. The proposed scheme is implemented on the TinyOS operating system. Simulation results showed that the proposed technique outperforms the existing schemes in terms of efficiency and security

Mot-clés: Internet of Things (IoT), Identity Management (IDM), Privacy, Fuzzy Vault, Fingerprint, Elliptic Curve Cryptography (ECC), ELGamal, Shamir Secret Sharing (SSS), Fog.