University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Introduction a Unix / John Halamka
Titre : Introduction a Unix Type de document : texte imprimé Auteurs : John Halamka Editeur : Paris : Sybex Année de publication : 1985 Importance : 1 vol. (234 p.) Format : 23 cm ISBN/ISSN/EAN : 2-7361-0098-1 Langues : Français (fre) Catégories : Informatique Mots-clés : Informatique
UnixIndex. décimale : 004 Informatique Note de contenu :
Sommaire
1- Concepts matériels et logiciels
2- Le concept unix
3- Utilisation de la coquille
4- L'administrateur du système
5- Programmer la coquille
6- Les outils matériels et logiciels
7- L'avenir d'unixCôte titre : Fs/8392 Introduction a Unix [texte imprimé] / John Halamka . - Paris : Sybex, 1985 . - 1 vol. (234 p.) ; 23 cm.
ISSN : 2-7361-0098-1
Langues : Français (fre)
Catégories : Informatique Mots-clés : Informatique
UnixIndex. décimale : 004 Informatique Note de contenu :
Sommaire
1- Concepts matériels et logiciels
2- Le concept unix
3- Utilisation de la coquille
4- L'administrateur du système
5- Programmer la coquille
6- Les outils matériels et logiciels
7- L'avenir d'unixCôte titre : Fs/8392 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité Fs/8392 Fs/8392 livre Bibliothéque des sciences Français Disponible
DisponibleIntrusion detection for the Internet of Things using deep learning techniques / nour el imene Lakabi
Titre : Intrusion detection for the Internet of Things using deep learning techniques Type de document : texte imprimé Auteurs : nour el imene Lakabi, Auteur ; Heithem Zeroual, Auteur ; Samir Fenanir, Directeur de thèse Année de publication : 2023 Importance : 1 vol (69 f .) Format : 29cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things (IoT)
intrusion detectionIndex. décimale : 004 Informatique Résumé : In response to the increasing concerns about security in the Internet of Things (IoT), this study focuses on addressing the crucial issue of intrusion detection using deep learning techniques. The primary goal is to develop effective and reliable intrusion detection systems capable of accurately identifying intrusions in IoT networks. The research begins by providing an in-depth introduction to the IoT, encompassing its architecture, data flow, components, and application areas. Key challenges faced by the IoT, including security, interoperability, scalability, and energy efficiency, are highlighted. Emphasis is placed on the importance of IoT security, vulnerabilities, and the various types of attacks that can occur. Intrusion Detection Systems (IDS), such as signature-based, anomaly-based, and specification-based IDS, are introduced as essential tools for detecting and mitigating intrusions. The thesis presents the implementation of three deep learning-based intrusion detection programs (DNN, CNN, and RNN) using the PyTorch library, with the effectiveness of these programs evaluated using the IoTID20 dataset. By harnessing deep learning techniques, this research contributes to enhancing the understanding and effectiveness of intrusion detection in IoT networks. Côte titre : MAI/0707 En ligne : https://drive.google.com/file/d/1m2FHecjMZFFPzXSDnF_pmOhCPeKjSQYh/view?usp=drive [...] Format de la ressource électronique : Intrusion detection for the Internet of Things using deep learning techniques [texte imprimé] / nour el imene Lakabi, Auteur ; Heithem Zeroual, Auteur ; Samir Fenanir, Directeur de thèse . - 2023 . - 1 vol (69 f .) ; 29cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things (IoT)
intrusion detectionIndex. décimale : 004 Informatique Résumé : In response to the increasing concerns about security in the Internet of Things (IoT), this study focuses on addressing the crucial issue of intrusion detection using deep learning techniques. The primary goal is to develop effective and reliable intrusion detection systems capable of accurately identifying intrusions in IoT networks. The research begins by providing an in-depth introduction to the IoT, encompassing its architecture, data flow, components, and application areas. Key challenges faced by the IoT, including security, interoperability, scalability, and energy efficiency, are highlighted. Emphasis is placed on the importance of IoT security, vulnerabilities, and the various types of attacks that can occur. Intrusion Detection Systems (IDS), such as signature-based, anomaly-based, and specification-based IDS, are introduced as essential tools for detecting and mitigating intrusions. The thesis presents the implementation of three deep learning-based intrusion detection programs (DNN, CNN, and RNN) using the PyTorch library, with the effectiveness of these programs evaluated using the IoTID20 dataset. By harnessing deep learning techniques, this research contributes to enhancing the understanding and effectiveness of intrusion detection in IoT networks. Côte titre : MAI/0707 En ligne : https://drive.google.com/file/d/1m2FHecjMZFFPzXSDnF_pmOhCPeKjSQYh/view?usp=drive [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0707 MAI/0707 livre Bibliothéque des sciences Anglais Disponible
DisponibleIntrusion detection for the Internet of Things using deep Learning techniques / Lameche, Mohamed Houssem Eddine
Titre : Intrusion detection for the Internet of Things using deep Learning techniques Type de document : texte imprimé Auteurs : Lameche, Mohamed Houssem Eddine, Auteur ; Fenanir,Samir, Directeur de thèse Editeur : Setif:UFA Année de publication : 2021 Importance : 1 vol (62 f .) Format : 29 cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things (IoT)
Intrusion Detection System (IDS)Index. décimale : 004 Informatique Résumé :
The IoT is a vast network that includes various smart devices and sensors, these "Things" collect and exchange data, but on the other hand, the risks and chances of malicious intrusions have increased and security has become a major issue in the management of corporate networks.
The intrusion is any breach of security of a computer system, and to address this issue, the intrusion detection system (IDS) is widely deployed as a second block of defense when the access control fails.
In this work, we present an anomaly-based IDS in the IoT environment using deep learning algorithms to design and implement technical and software architecture in an IoT context that makes its defense more effective in classifying attacks than normal use by building a semi-supervised deep autoencoder (SDEA) model which extracts the basic features of the normal use in latent content, so in the case of an attack, it compares the attack features with the normal features and because of the difference who crosses the threshold, it will be classified as an attack.Côte titre : MAI/0517 En ligne : https://drive.google.com/file/d/11IRUm3hKprY7pbEME-9U--QRbELbZgf4/view?usp=shari [...] Format de la ressource électronique : Intrusion detection for the Internet of Things using deep Learning techniques [texte imprimé] / Lameche, Mohamed Houssem Eddine, Auteur ; Fenanir,Samir, Directeur de thèse . - [S.l.] : Setif:UFA, 2021 . - 1 vol (62 f .) ; 29 cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Internet of Things (IoT)
Intrusion Detection System (IDS)Index. décimale : 004 Informatique Résumé :
The IoT is a vast network that includes various smart devices and sensors, these "Things" collect and exchange data, but on the other hand, the risks and chances of malicious intrusions have increased and security has become a major issue in the management of corporate networks.
The intrusion is any breach of security of a computer system, and to address this issue, the intrusion detection system (IDS) is widely deployed as a second block of defense when the access control fails.
In this work, we present an anomaly-based IDS in the IoT environment using deep learning algorithms to design and implement technical and software architecture in an IoT context that makes its defense more effective in classifying attacks than normal use by building a semi-supervised deep autoencoder (SDEA) model which extracts the basic features of the normal use in latent content, so in the case of an attack, it compares the attack features with the normal features and because of the difference who crosses the threshold, it will be classified as an attack.Côte titre : MAI/0517 En ligne : https://drive.google.com/file/d/11IRUm3hKprY7pbEME-9U--QRbELbZgf4/view?usp=shari [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0517 MAI/0517 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
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 : IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) : Performances Evaluation Type de document : texte imprimé Auteurs : Nour El Islem Yaakoub Fortas, Auteur ; Mohamd Nour El Islam Chaalal, Auteur ; Houssem Mansouri, Directeur de thèse Année de publication : 2022 Importance : 1 vol (69 f .) Format : 29cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Routing protocol
RPLIndex. décimale : 004 Informatique Résumé :
In this project, we are interested in the question of routing in the Internet of
Things (IoT) and more particularly in the routing protocol for low-power and
lossy networks (RPL). The objectives of the project initially are to understand
the context and the key concepts related to IoT, and in a second stage,
we describe routing techniques in the IoT as well as the study of existing
important routing protocols. Then, we will presents RPL protocol operating
and function details. Finally, the last part is an experimental study where we
will evaluate RPL performance using the Cooja simulator, in terms of Energy
and Packet Delivery according to two routing metrics: the Expected Transmission
Count ETX and the Energy consumption, and under two topologies
random and grid. Where the results obtained shown that the advantage of
the grid topology over the other scheme is that the energy consumption is
relatively lesser as the numbers of nodes in the system increase.Côte titre : MAI/0683 En ligne : https://drive.google.com/file/d/1iIYFu6sXjDd73ZrNYX2ImRGmxhqnaeox/view?usp=share [...] Format de la ressource électronique : IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) : Performances Evaluation [texte imprimé] / Nour El Islem Yaakoub Fortas, Auteur ; Mohamd Nour El Islam Chaalal, Auteur ; Houssem Mansouri, Directeur de thèse . - 2022 . - 1 vol (69 f .) ; 29cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Routing protocol
RPLIndex. décimale : 004 Informatique Résumé :
In this project, we are interested in the question of routing in the Internet of
Things (IoT) and more particularly in the routing protocol for low-power and
lossy networks (RPL). The objectives of the project initially are to understand
the context and the key concepts related to IoT, and in a second stage,
we describe routing techniques in the IoT as well as the study of existing
important routing protocols. Then, we will presents RPL protocol operating
and function details. Finally, the last part is an experimental study where we
will evaluate RPL performance using the Cooja simulator, in terms of Energy
and Packet Delivery according to two routing metrics: the Expected Transmission
Count ETX and the Energy consumption, and under two topologies
random and grid. Where the results obtained shown that the advantage of
the grid topology over the other scheme is that the energy consumption is
relatively lesser as the numbers of nodes in the system increase.Côte titre : MAI/0683 En ligne : https://drive.google.com/file/d/1iIYFu6sXjDd73ZrNYX2ImRGmxhqnaeox/view?usp=share [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0683 MAI/0683 Mémoire Bibliothéque des sciences Anglais Disponible
DisponibleJob Shop Scheduling with Consideration of Due Dates / Jens Kuhpfahl
PermalinkLe jumeau numérique / Nathalie Julien
PermalinkLabVIEW / COTTET,Francis
PermalinkLateX companion / Frank Mittelbach
PermalinkLexique D'informatique des mots et des idées / Jeanne Milsant
PermalinkLinked data / Tom Heath
PermalinkLinux / Pinchon, Philippe
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