University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Titre : IoT Security in Healthcare Type de document : texte imprimé Auteurs : Azzouz Merouani ; Loubna Kacher ; Habib Aissaoua, Directeur de thèse Editeur : Setif:UFA Année de publication : 2023 Importance : 1 vol. (70 f.) Format : 29 cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things Internet of Medical Things Blockchain Fog Computing Homomorphic Encryption Index. décimale : 004 Informatique Résumé : The rapid growth of interconnected medical devices poses significant challenges in protecting
sensitive patient data and ensuring secure data transmission and computation.
To address these challenges, we propose a novel framework that combines Blockchain
technology, Homomorphic encryption, and Fog computing. Also, we conducted comprehensive
security and performance analyses to evaluate the effectiveness of our proposed
framework. The security analysis shows that our solution is resilient against various
common attacks, including data breaches, tampering, and insider attacks. Furthermore,
we assessed the performance of the framework by considering factors such as
key size, number of variables, and network communication methods. The results of
experiments show that our solution has good robustness in protecting sensitive medical
data and maintaining data integrity throughout the IoMT ecosystem. As a result,
the combination of blockchain, homomorphic encryption, and fog computing offers a
comprehensive solution to address security and privacy concerns in IoMT systemsCôte titre : MAI/0744 En ligne : https://drive.google.com/file/d/1rbjY4WiIVumGQ5VvWn0YZV3VpekFHMeW/view?usp=drive [...] Format de la ressource électronique : IoT Security in Healthcare [texte imprimé] / Azzouz Merouani ; Loubna Kacher ; Habib Aissaoua, Directeur de thèse . - [S.l.] : Setif:UFA, 2023 . - 1 vol. (70 f.) ; 29 cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things Internet of Medical Things Blockchain Fog Computing Homomorphic Encryption Index. décimale : 004 Informatique Résumé : The rapid growth of interconnected medical devices poses significant challenges in protecting
sensitive patient data and ensuring secure data transmission and computation.
To address these challenges, we propose a novel framework that combines Blockchain
technology, Homomorphic encryption, and Fog computing. Also, we conducted comprehensive
security and performance analyses to evaluate the effectiveness of our proposed
framework. The security analysis shows that our solution is resilient against various
common attacks, including data breaches, tampering, and insider attacks. Furthermore,
we assessed the performance of the framework by considering factors such as
key size, number of variables, and network communication methods. The results of
experiments show that our solution has good robustness in protecting sensitive medical
data and maintaining data integrity throughout the IoMT ecosystem. As a result,
the combination of blockchain, homomorphic encryption, and fog computing offers a
comprehensive solution to address security and privacy concerns in IoMT systemsCôte titre : MAI/0744 En ligne : https://drive.google.com/file/d/1rbjY4WiIVumGQ5VvWn0YZV3VpekFHMeW/view?usp=drive [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0744 MAI/0744 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
Titre : Task offloading, Scheduling and Resource Allocation Type de document : texte imprimé Auteurs : Maroua Rehahla ; Fatima Zohra Saadoune ; Djamila Mechta, Directeur de thèse Editeur : Setif:UFA Année de publication : 2023 Importance : 1 vol. (66 f.) Format : 29 cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things Edge Computing Task Scheduling Resource Allocation Optimization Index. décimale : 004 Informatique Résumé : Task offloading, scheduling and resource allocation are the main elements of edge computing.
This Master thesis aims to find a new technique to do the offloading, the task scheduling, and the resource
allocation, based on artificial intelligence (AI). we will talk about the main definitions, concepts, analyzes
and discusses some surveys and related works to offloading, task scheduling and resource allocation. Our
contribution is proposed a new hybrid method for task offloading and resource allocation based on artificial
intelligence (AI) especially the K-means algorithm (KMA) for the offloading decision and the genetic algorithm
(GA) for the scheduling and resources allocation. Finally, this method takes advantages of both the artificial
intelligence (k-means clustering) and genetic algorithm (GA) to optimize the makespan, the bandwidth and
the energy consumption. After comparing our work with authors works, we have found that our proposed is
we notice that the proposed algorithm is efficient in terms of makespan, bandwidth and energy consumptionCôte titre : MAI/0749 En ligne : https://drive.google.com/file/d/1RvsRQn9ecY65LzPjLco6gwyt0IDoU3uL/view?usp=drive [...] Format de la ressource électronique : Task offloading, Scheduling and Resource Allocation [texte imprimé] / Maroua Rehahla ; Fatima Zohra Saadoune ; Djamila Mechta, Directeur de thèse . - [S.l.] : Setif:UFA, 2023 . - 1 vol. (66 f.) ; 29 cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things Edge Computing Task Scheduling Resource Allocation Optimization Index. décimale : 004 Informatique Résumé : Task offloading, scheduling and resource allocation are the main elements of edge computing.
This Master thesis aims to find a new technique to do the offloading, the task scheduling, and the resource
allocation, based on artificial intelligence (AI). we will talk about the main definitions, concepts, analyzes
and discusses some surveys and related works to offloading, task scheduling and resource allocation. Our
contribution is proposed a new hybrid method for task offloading and resource allocation based on artificial
intelligence (AI) especially the K-means algorithm (KMA) for the offloading decision and the genetic algorithm
(GA) for the scheduling and resources allocation. Finally, this method takes advantages of both the artificial
intelligence (k-means clustering) and genetic algorithm (GA) to optimize the makespan, the bandwidth and
the energy consumption. After comparing our work with authors works, we have found that our proposed is
we notice that the proposed algorithm is efficient in terms of makespan, bandwidth and energy consumptionCôte titre : MAI/0749 En ligne : https://drive.google.com/file/d/1RvsRQn9ecY65LzPjLco6gwyt0IDoU3uL/view?usp=drive [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0749 MAI/0749 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible