University Sétif 1 FERHAT ABBAS Faculty of Sciences
Détail de l'auteur
Auteur Goudjil, Lakhdar |
Documents disponibles écrits par cet auteur
Ajouter le résultat dans votre panier Affiner la rechercheBlockchain-based deep learning to improve the security of the Industrial Internet of Things / Aya Bendjedi
Titre : Blockchain-based deep learning to improve the security of the Industrial Internet of Things Type de document : texte imprimé Auteurs : Aya Bendjedi, Auteur ; Chems Zerguine ; Goudjil, Lakhdar, Directeur de thèse Editeur : Setif:UFA Année de publication : 2024 Importance : 1 vol (99 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : IIoT
Blockchain
BIIoT
Deep Learning
X-IIOTID
WUSTL-IIoT-2021
Edge- IIoTset.Index. décimale : 004 - Informatique Résumé :
The integration of blockchain development of advanced solutions for se- and deep learning technologies holds signi- cure data exchange, anomaly detection, and ficant promise in enhancing the security of threat mitigation, we aim to bolster the se- Industrial Internet of Things (IIoT) systems. curity of IIoT networks. Prototype systems This paper explores the potential of leveraging are designed and implemented to showcaseblockchain- based deep learning approaches to the practical application of blockchain-based address the unique security challenges faced deep learning in IIoT security, with evalua- by IIoT deployments. We propose novel ar- tions conducted in real-world industrial set- chitectures and algorithms tailored to seam- tings using the aforementioned datasets. Our lessly integrate blockchain and deep learning findings demonstrate the effectiveness of inte- techniques into IIoT environments, focusing grating blockchain and deep learning metho- on datasets representative of Edge IIoTset, dologies, highlighting improvements in secu- WUSTL-IIoT- 2021, and X-IIoTID. Through the rity, accuracy, and scalability in IIoT environ-
ments.Note de contenu : Sommaire
General Introduction 1
0.1 Genral Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
0.1.1 Context and Motivation . . . . . . . . . . . . . . . . . . . . . . . . 1
0.1.2 Objectives and Contributions . . . . . . . . . . . . . . . . . . . . . 1
0.1.3 Organization of the Manuscript . . . . . . . . . . . . . . . . . . . . 2
1 the Basic Concepts of IoT and IIoT 3
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 IoT History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 IoT Architecture Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 Three-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . 6
1.4.2 Five-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Features of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6 Domains of Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.1 Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.2 Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.3 Smart Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.4 Healthcare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.7 Benefits of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.8 Disadvantages of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.9 Definition of IIoT .............................................................................................. 10
1.10 Transformation of IoT to IIoT ............................................................................ 10
1.11 Milestones of IIoT ............................................................................................. 10
1.12 IIoT challenges .................................................................................................. 11
1.13 IIoT Architecture ............................................................................................... 12
1.14 Industrial IoT and Industry 4.0 ........................................................................... 13
1.15 Foundations of the IIoT ..................................................................................... 14
1.16 The Scope of Application of the IIoT................................................................. 14
1.17 Conclusion ........................................................................................................ 14
2 Blockchain in Industrial Internet of Things (IIoT) 17
2.1 Introduction ...................................................................................................... 18
2.2 Definition of Blockchain ................................................................................... 18
2.3 History of Blockchain ....................................................................................... 18
2.4 Blockchain Functionalities and Implications ..................................................... 19
2.5 Applications of Blockchain ............................................................................... 20
2.6 Blockchain Key Characteristics......................................................................... 20
2.7 Types and Taxonomy of Blockchain Systems .................................................... 22
2.7.1 Types of Blockchain ............................................................................. 22
2.7.2 Comparison of Blockchain Types ......................................................... 22
2.8 Blockchain Infrastructure .................................................................................. 23
2.9 Working Of a Blockchain.................................................................................. 26
2.10 Blockchain -IIOT Challenges ............................................................................ 26
2.11 Potential Solutions to Blockchain-IIoT Challenges ........................................... 27
2.12 Chances of combining IIoT with blockchain ..................................................... 28
2.13 Architecture of BIIoT ........................................................................................ 29
2.14 BIIoT applications ............................................................................................ 30
2.14.1 Food sector ........................................................................................... 31
2.14.2 Smart manufacturing sector .................................................................. 31
2.14.3 Healthcare sector .................................................................................. 31
2.14.4 Automotive Industry ............................................................................. 31
2.14.5 Oil and gas sector.................................................................................. 32
2.14.6 Trade supply chain industry ................................................................ 32
2.15 BIIoT open research issues ................................................................................ 32
2.15.1 Privacy leakage ..................................................................................... 33
2.15.2 Security vulnerability ............................................................................ 33
2.15.3 Constraints of resources ........................................................................ 33
2.15.4 Scalability............................................................................................. 34
2.15.5 Big data difficulty ................................................................................. 34
2.16 Conclusion ........................................................................................................ 35
3 Machine Learning and Deep Learning 37
3.1 Introduction ...................................................................................................... 38
3.2 Definition of Machine Learning ........................................................................ 38
3.3 Renaissance of Machine Learning .................................................................... 38
3.4 Types of Machine Learning ............................................................................... 39
3.4.1 Supervised Learning ............................................................................. 39
3.4.2 Unsupervised Learning ......................................................................... 40
3.4.3 Semi-Supervised Learning .................................................................... 41
3.4.4 Reinforcement Learning ....................................................................... 41
3.5 Deep Learning .................................................................................................. 43
3.6 Layers of a neural network ................................................................................ 44
3.7 Activation Functions ......................................................................................... 45
3.8 Machine Learning vs Deep Learning................................................................. 45
3.9 Applications of Deep Learning .......................................................................... 46
3.10 Areas of Deep Learning System ........................................................................ 46
3.11 Deep Learning Architectures ............................................................................ 47
3.11.1 Convolutional neural networks (CNNs) ................................................ 47
3.11.2 Recurrent neural networks (RNNs) ....................................................... 47
3.11.3 Deep Neural Network (DNN) ................................................................ 48
3.12 DEEP LEARNING FOR THE IIOT ............................................................................ 48
3.13 Introduction ....................................................................................................... 50
3.14 Blockchain-based deep learning ........................................................................ 51
3.15 Blockchain-based Deep learning Application areas ........................................... 53
3.15.1 Healthcare ............................................................................................. 53
3.15.2 Internet of vehicles ................................................................................ 53
3.15.3 Traffic management .............................................................................. 54
3.15.4 Safety and protection............................................................................. 54
3.16 Blockchain-based Deep learning Services .......................................................... 54
3.16.1 Privacy preservation ............................................................................. 55
3.16.2 Violation prediction .............................................................................. 55
3.16.3 Anomaly detection ................................................................................ 55
3.16.4 Data traffic management ....................................................................... 55
3.16.5 Forking prevention ............................................................................... 55
3.16.6 EHR forecasting .................................................................................... 56
3.17 Blockchain-based Deep learningData types ....................................................... 56
3.17.1 Image data CNN.................................................................................... 56
3.17.2 Textual data Textual .............................................................................. 56
3.18 Blockchain-based Deep learning Deployment goal............................................ 56
3.18.1 Trusted AI models ................................................................................. 57
3.18.2 AI decisions sharing .............................................................................. 57
3.19 Conclusion ........................................................................................................ 58
4 Blockchain-Based Deep Learning to Improve the Security of the Industrial Internet of Things 59
4.1 Introduction ....................................................................................................... 63
4.2 A Novel Privacy-Preserving and Secure Framework (PPSS) for Industry 4.0/5.0
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.2.1 Definition and Proposed Method........................................................... 63
4.3 Integrating Deep Learning and Blockchain to Secure Industrial IoT Net- works from Cyberattacks .................................................................................. 63
4.3.1 Definition of intrusion detection system (IDS) ....................................... 63
4.4 Differences and similarities ............................................................................... 64
4.5 Dataset in IIoT................................................................................................... 65
4.6 Description of Edge-IIoTset ........................................................................................ 68
4.7 Attacks EDGE-IIoTset Dataset .................................................................................... 68
4.7.1 Attaques DoS/DDoS ............................................................................. 68
4.7.2 Information Collection .......................................................................... 68
4.8 Man in the middle attack .................................................................................. 69
4.9
Malware Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
69
4.10
Description of WUSTL-IIoT-2021 . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11
Attacks in WUSTL-IIoT-2021 Dataset . . . . . . . . . . . . . . . . . . . . .
71
4.11.1 Denial-of-Service (DoS) Attacks . . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.2 Reconnaissance Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.3 Command Injection Attacks . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.4 Backdoor Attacks . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .
71
4.12
Description of X-IIoTID . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13
Number of Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.1 Class 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.2 Class 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.3 Class 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14
Attacks in X-IIoTID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.1 Denial-of-Service (DoS) Attacks . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.2ScanningAttacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.3 Brute-Force Attacks (Attaque BruteForce) . . . . . . . . . . . . . .
74
4.14.4 MQTT_cloud_broker_subscription Attack . . . . . . . . . . . . . .
74
4.14.5 Discovering_resources Attack . . . . . . . . . . . . . . . . . . . . .
74
4.14.6 Exfiltration Attack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
74
4.14.7 Insider_malicious Attack . . . . . . . . . . . . . . . . . . . . . . . .
74
4.14.8 Modbus_register_reading Attack . . . . . . . . . . . . . . . . . . .
74
4.14.9 False_data_injection Attack . . . . . . . . . . . . . . . . . . . . . .
74
4.14.10 Command and Control (C&C) Attack . . . . . . . . . . . . . . . . .
75
4.14.11 Dictionary Attack (Attaque Dictionary) . . . . . . . . . . . . . . .
75
4.14.12 TCP Relay Attack (Attaque TCP Relay) . . . . . . . . . . . . . . . .
75
4.14.13 Fuzzing Attack (Attaque fuzzing) . . . . . . . . . . . . . . . . . . .
75
4.14.14 Reverse_shell Attack . . . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.15 Man-in-the-Middle (MitM) Attack . . . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.16 Fake Notification Attack . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.17 Cryptoransomware Attack . . . . . . . . . . . . . . . . . . . . . . .
75
4.15
Visual Display for Three Different Kinds of Datasets . . . . . . . . . . . . .
79
4.15.1 Heatmap Correlation of Numerical Features . . . . . . . . . . . . .
79
4.16
Top Attack Types Displayed in a Bar Chart . . . . . . . . . . . . . . . . . .
81
4.17
Distribution of Attack Types in the Dataset . . . . . . . . . . . . . . . . . .
83
4.17.1 1) Distribution of Attack Types in the Edge-IIoT Dataset . . . . . .
83
4.17.2 Distribution of Attack Types in the X-IIOTID Dataset . . . . . . . .
84
4.17.3 Exploring Data Distribution through Histograms . . . . . . . . . .
87
4.18
Application of DNN Models in IIoT Datasets . . . . . . . . . . . . . . . . .
90
4.18.1 Classification Report of the Model in Dataset . . . . . . . . . . . .
91
4.19
Integrate Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
94
4.19.1 Why Integrate Blockchain . . . . . . . . . . . . . . . . . . . . . . .
94
4.19.2 How to Integrate Blockchain with a Deep Learning Model . . . . .
94
4.19.3 Blockchain details in Edge-IIoT . . . . . . . . . . . . . . . . . . . .
95
4.19.4 Blockchain details in X-IIOTID . . . . . . . . . . . . . . . . . . . .
95
4.19.5 Blockchain details in Wustl-IIoT . . . . . . . . . . . . . . . . . . .
964.19.6 Accuracy ............................................................................................... 96
4.19.7 Macro Average ..................................................................................... 96
4.19.8 Weighted Average ................................................................................. 97
4.20 Conclusion ........................................................................................................ 97
Côte titre : MAI/0925
Blockchain-based deep learning to improve the security of the Industrial Internet of Things [texte imprimé] / Aya Bendjedi, Auteur ; Chems Zerguine ; Goudjil, Lakhdar, Directeur de thèse . - [S.l.] : Setif:UFA, 2024 . - 1 vol (99 f .) ; 29 cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : IIoT
Blockchain
BIIoT
Deep Learning
X-IIOTID
WUSTL-IIoT-2021
Edge- IIoTset.Index. décimale : 004 - Informatique Résumé :
The integration of blockchain development of advanced solutions for se- and deep learning technologies holds signi- cure data exchange, anomaly detection, and ficant promise in enhancing the security of threat mitigation, we aim to bolster the se- Industrial Internet of Things (IIoT) systems. curity of IIoT networks. Prototype systems This paper explores the potential of leveraging are designed and implemented to showcaseblockchain- based deep learning approaches to the practical application of blockchain-based address the unique security challenges faced deep learning in IIoT security, with evalua- by IIoT deployments. We propose novel ar- tions conducted in real-world industrial set- chitectures and algorithms tailored to seam- tings using the aforementioned datasets. Our lessly integrate blockchain and deep learning findings demonstrate the effectiveness of inte- techniques into IIoT environments, focusing grating blockchain and deep learning metho- on datasets representative of Edge IIoTset, dologies, highlighting improvements in secu- WUSTL-IIoT- 2021, and X-IIoTID. Through the rity, accuracy, and scalability in IIoT environ-
ments.Note de contenu : Sommaire
General Introduction 1
0.1 Genral Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
0.1.1 Context and Motivation . . . . . . . . . . . . . . . . . . . . . . . . 1
0.1.2 Objectives and Contributions . . . . . . . . . . . . . . . . . . . . . 1
0.1.3 Organization of the Manuscript . . . . . . . . . . . . . . . . . . . . 2
1 the Basic Concepts of IoT and IIoT 3
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 IoT History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 IoT Architecture Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 Three-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . 6
1.4.2 Five-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Features of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6 Domains of Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.1 Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.2 Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.3 Smart Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.4 Healthcare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.7 Benefits of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.8 Disadvantages of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.9 Definition of IIoT .............................................................................................. 10
1.10 Transformation of IoT to IIoT ............................................................................ 10
1.11 Milestones of IIoT ............................................................................................. 10
1.12 IIoT challenges .................................................................................................. 11
1.13 IIoT Architecture ............................................................................................... 12
1.14 Industrial IoT and Industry 4.0 ........................................................................... 13
1.15 Foundations of the IIoT ..................................................................................... 14
1.16 The Scope of Application of the IIoT................................................................. 14
1.17 Conclusion ........................................................................................................ 14
2 Blockchain in Industrial Internet of Things (IIoT) 17
2.1 Introduction ...................................................................................................... 18
2.2 Definition of Blockchain ................................................................................... 18
2.3 History of Blockchain ....................................................................................... 18
2.4 Blockchain Functionalities and Implications ..................................................... 19
2.5 Applications of Blockchain ............................................................................... 20
2.6 Blockchain Key Characteristics......................................................................... 20
2.7 Types and Taxonomy of Blockchain Systems .................................................... 22
2.7.1 Types of Blockchain ............................................................................. 22
2.7.2 Comparison of Blockchain Types ......................................................... 22
2.8 Blockchain Infrastructure .................................................................................. 23
2.9 Working Of a Blockchain.................................................................................. 26
2.10 Blockchain -IIOT Challenges ............................................................................ 26
2.11 Potential Solutions to Blockchain-IIoT Challenges ........................................... 27
2.12 Chances of combining IIoT with blockchain ..................................................... 28
2.13 Architecture of BIIoT ........................................................................................ 29
2.14 BIIoT applications ............................................................................................ 30
2.14.1 Food sector ........................................................................................... 31
2.14.2 Smart manufacturing sector .................................................................. 31
2.14.3 Healthcare sector .................................................................................. 31
2.14.4 Automotive Industry ............................................................................. 31
2.14.5 Oil and gas sector.................................................................................. 32
2.14.6 Trade supply chain industry ................................................................ 32
2.15 BIIoT open research issues ................................................................................ 32
2.15.1 Privacy leakage ..................................................................................... 33
2.15.2 Security vulnerability ............................................................................ 33
2.15.3 Constraints of resources ........................................................................ 33
2.15.4 Scalability............................................................................................. 34
2.15.5 Big data difficulty ................................................................................. 34
2.16 Conclusion ........................................................................................................ 35
3 Machine Learning and Deep Learning 37
3.1 Introduction ...................................................................................................... 38
3.2 Definition of Machine Learning ........................................................................ 38
3.3 Renaissance of Machine Learning .................................................................... 38
3.4 Types of Machine Learning ............................................................................... 39
3.4.1 Supervised Learning ............................................................................. 39
3.4.2 Unsupervised Learning ......................................................................... 40
3.4.3 Semi-Supervised Learning .................................................................... 41
3.4.4 Reinforcement Learning ....................................................................... 41
3.5 Deep Learning .................................................................................................. 43
3.6 Layers of a neural network ................................................................................ 44
3.7 Activation Functions ......................................................................................... 45
3.8 Machine Learning vs Deep Learning................................................................. 45
3.9 Applications of Deep Learning .......................................................................... 46
3.10 Areas of Deep Learning System ........................................................................ 46
3.11 Deep Learning Architectures ............................................................................ 47
3.11.1 Convolutional neural networks (CNNs) ................................................ 47
3.11.2 Recurrent neural networks (RNNs) ....................................................... 47
3.11.3 Deep Neural Network (DNN) ................................................................ 48
3.12 DEEP LEARNING FOR THE IIOT ............................................................................ 48
3.13 Introduction ....................................................................................................... 50
3.14 Blockchain-based deep learning ........................................................................ 51
3.15 Blockchain-based Deep learning Application areas ........................................... 53
3.15.1 Healthcare ............................................................................................. 53
3.15.2 Internet of vehicles ................................................................................ 53
3.15.3 Traffic management .............................................................................. 54
3.15.4 Safety and protection............................................................................. 54
3.16 Blockchain-based Deep learning Services .......................................................... 54
3.16.1 Privacy preservation ............................................................................. 55
3.16.2 Violation prediction .............................................................................. 55
3.16.3 Anomaly detection ................................................................................ 55
3.16.4 Data traffic management ....................................................................... 55
3.16.5 Forking prevention ............................................................................... 55
3.16.6 EHR forecasting .................................................................................... 56
3.17 Blockchain-based Deep learningData types ....................................................... 56
3.17.1 Image data CNN.................................................................................... 56
3.17.2 Textual data Textual .............................................................................. 56
3.18 Blockchain-based Deep learning Deployment goal............................................ 56
3.18.1 Trusted AI models ................................................................................. 57
3.18.2 AI decisions sharing .............................................................................. 57
3.19 Conclusion ........................................................................................................ 58
4 Blockchain-Based Deep Learning to Improve the Security of the Industrial Internet of Things 59
4.1 Introduction ....................................................................................................... 63
4.2 A Novel Privacy-Preserving and Secure Framework (PPSS) for Industry 4.0/5.0
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.2.1 Definition and Proposed Method........................................................... 63
4.3 Integrating Deep Learning and Blockchain to Secure Industrial IoT Net- works from Cyberattacks .................................................................................. 63
4.3.1 Definition of intrusion detection system (IDS) ....................................... 63
4.4 Differences and similarities ............................................................................... 64
4.5 Dataset in IIoT................................................................................................... 65
4.6 Description of Edge-IIoTset ........................................................................................ 68
4.7 Attacks EDGE-IIoTset Dataset .................................................................................... 68
4.7.1 Attaques DoS/DDoS ............................................................................. 68
4.7.2 Information Collection .......................................................................... 68
4.8 Man in the middle attack .................................................................................. 69
4.9
Malware Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
69
4.10
Description of WUSTL-IIoT-2021 . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11
Attacks in WUSTL-IIoT-2021 Dataset . . . . . . . . . . . . . . . . . . . . .
71
4.11.1 Denial-of-Service (DoS) Attacks . . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.2 Reconnaissance Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.3 Command Injection Attacks . . . . . . . . . . . . . . . . . . . . . . .
71
4.11.4 Backdoor Attacks . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .
71
4.12
Description of X-IIoTID . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13
Number of Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.1 Class 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.2 Class 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.13.3 Class 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14
Attacks in X-IIoTID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.1 Denial-of-Service (DoS) Attacks . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.2ScanningAttacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
4.14.3 Brute-Force Attacks (Attaque BruteForce) . . . . . . . . . . . . . .
74
4.14.4 MQTT_cloud_broker_subscription Attack . . . . . . . . . . . . . .
74
4.14.5 Discovering_resources Attack . . . . . . . . . . . . . . . . . . . . .
74
4.14.6 Exfiltration Attack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
74
4.14.7 Insider_malicious Attack . . . . . . . . . . . . . . . . . . . . . . . .
74
4.14.8 Modbus_register_reading Attack . . . . . . . . . . . . . . . . . . .
74
4.14.9 False_data_injection Attack . . . . . . . . . . . . . . . . . . . . . .
74
4.14.10 Command and Control (C&C) Attack . . . . . . . . . . . . . . . . .
75
4.14.11 Dictionary Attack (Attaque Dictionary) . . . . . . . . . . . . . . .
75
4.14.12 TCP Relay Attack (Attaque TCP Relay) . . . . . . . . . . . . . . . .
75
4.14.13 Fuzzing Attack (Attaque fuzzing) . . . . . . . . . . . . . . . . . . .
75
4.14.14 Reverse_shell Attack . . . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.15 Man-in-the-Middle (MitM) Attack . . . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.16 Fake Notification Attack . . . . . . . . . . . . . . . . . . . . . . . .
75
4.14.17 Cryptoransomware Attack . . . . . . . . . . . . . . . . . . . . . . .
75
4.15
Visual Display for Three Different Kinds of Datasets . . . . . . . . . . . . .
79
4.15.1 Heatmap Correlation of Numerical Features . . . . . . . . . . . . .
79
4.16
Top Attack Types Displayed in a Bar Chart . . . . . . . . . . . . . . . . . .
81
4.17
Distribution of Attack Types in the Dataset . . . . . . . . . . . . . . . . . .
83
4.17.1 1) Distribution of Attack Types in the Edge-IIoT Dataset . . . . . .
83
4.17.2 Distribution of Attack Types in the X-IIOTID Dataset . . . . . . . .
84
4.17.3 Exploring Data Distribution through Histograms . . . . . . . . . .
87
4.18
Application of DNN Models in IIoT Datasets . . . . . . . . . . . . . . . . .
90
4.18.1 Classification Report of the Model in Dataset . . . . . . . . . . . .
91
4.19
Integrate Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
94
4.19.1 Why Integrate Blockchain . . . . . . . . . . . . . . . . . . . . . . .
94
4.19.2 How to Integrate Blockchain with a Deep Learning Model . . . . .
94
4.19.3 Blockchain details in Edge-IIoT . . . . . . . . . . . . . . . . . . . .
95
4.19.4 Blockchain details in X-IIOTID . . . . . . . . . . . . . . . . . . . .
95
4.19.5 Blockchain details in Wustl-IIoT . . . . . . . . . . . . . . . . . . .
964.19.6 Accuracy ............................................................................................... 96
4.19.7 Macro Average ..................................................................................... 96
4.19.8 Weighted Average ................................................................................. 97
4.20 Conclusion ........................................................................................................ 97
Côte titre : MAI/0925
Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0925 MAI/0925 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
Titre : Blockchain technology applications for Industry 4.0 Type de document : texte imprimé Auteurs : Djaouida Benkila, Auteur ; Goudjil, Lakhdar, Directeur de thèse Editeur : Sétif:UFA1 Année de publication : 2023 Importance : 1 vol (77f .) Format : 29cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Blockchain
Industry 4.0Index. décimale : 004 Informatique Résumé : Blockchain technology is transforming industries in the digital innovation landscape, including Industry 4.0 and the upcoming Industry 5.0. In Industry 4.0, blockchain enhances trust, security, and transparency by enabling secure record-keeping and decentralized networks. It streamlines operations and creates a more efficient ecosystem. In Industry 5.0, blockchain empowers individuals with control over digital identities, intellectual property, and financial transactions. Decentralized applications and smart contracts facilitate peer-to-peer interactions. Blockchain's impact extends beyond manufacturing to healthcare, finance, logistics, and energy, enhancing data sharing, cybersecurity, and trust. Its decentralized nature mitigates failures and safeguards sensitive information. In this study we Investigating the fundamentals of Industry 4.0, and industry 5.0 Its challenges, barriers, and limitations. Finally exploring areas where blockchain technology can bring new features and add value to the deployment of them. Côte titre : MAI/0714 En ligne : https://drive.google.com/file/d/1ugBW1k_VTIthmTVaE-B6zFGDTYfuTYKP/view?usp=drive [...] Format de la ressource électronique : Blockchain technology applications for Industry 4.0 [texte imprimé] / Djaouida Benkila, Auteur ; Goudjil, Lakhdar, Directeur de thèse . - [S.l.] : Sétif:UFA1, 2023 . - 1 vol (77f .) ; 29cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Blockchain
Industry 4.0Index. décimale : 004 Informatique Résumé : Blockchain technology is transforming industries in the digital innovation landscape, including Industry 4.0 and the upcoming Industry 5.0. In Industry 4.0, blockchain enhances trust, security, and transparency by enabling secure record-keeping and decentralized networks. It streamlines operations and creates a more efficient ecosystem. In Industry 5.0, blockchain empowers individuals with control over digital identities, intellectual property, and financial transactions. Decentralized applications and smart contracts facilitate peer-to-peer interactions. Blockchain's impact extends beyond manufacturing to healthcare, finance, logistics, and energy, enhancing data sharing, cybersecurity, and trust. Its decentralized nature mitigates failures and safeguards sensitive information. In this study we Investigating the fundamentals of Industry 4.0, and industry 5.0 Its challenges, barriers, and limitations. Finally exploring areas where blockchain technology can bring new features and add value to the deployment of them. Côte titre : MAI/0714 En ligne : https://drive.google.com/file/d/1ugBW1k_VTIthmTVaE-B6zFGDTYfuTYKP/view?usp=drive [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0714 MAI/0714 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
Titre : Enhancing IoT Security For Smart Homes Through blockchain Type de document : texte imprimé Auteurs : Hichem Maazouz, Auteur ; Haithem Berhail ; Goudjil, Lakhdar, Directeur de thèse Editeur : Setif:UFA Année de publication : 2024 Importance : 1 vol (80 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique
Enhancing IoT SecurityIndex. décimale : 004 - Informatique Résumé :
Integrating Internet of Things (IoT) technology into smart homes significantly advances home automation
and security. However, the proliferation of IoT devices introduces complex security vulnerabilities.
Blockchain technology, with its decentralized and secure nature, offers a promising solution.
This thesis introduces HomeChain, a blockchain-based security framework for smart homes, enhancing
data integrity, privacy, and access control in IoT networks. We analyze HomeChain’s architecture
and functionality and conduct a performance evaluation focusing on its effectiveness in mitigating
common smart home security threats. The results demonstrate blockchain’s potential to improve security
and operational efficiency in smart home IoT systems, positioning it as a leading candidate for
standardizing smart home security solutions.Note de contenu : Sommaire
GENERAL INTRODUCTION 1
Chapter1: IoT AND SMART HOME 2
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Architecture of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.1 Three layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.2 Five-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.3 Middle Ware Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.4 SoA Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 IoT layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 Perception layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.2 Network layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.3 Application Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Application of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.1 Smart Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.2 Healthcare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.3 Smart industrial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.4 Smart Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6 IoT Communication Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6.1 MQTT (Message Queue Telemetry Transport) . . . . . . . . . . . . . . . . 7
1.6.2 CoAP (Constrained Application Protocol) . . . . . . . . . . . . . . . . . . . 7
1.6.3 Extensible Messaging and Presence Protocol (XMPP) . . . . . . . . . . . . 8
1.7 Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.8 Main Issues and Challenges of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.1 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.2 Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.3 Interoperability and standards . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.8.4 Regulatory and rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.9 Smart Home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.10 How smart home works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.11 Different areas of application of smart home . . . . . . . . . . . . . . . . . . . . . . 13
1.11.1 Smart home for comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.11.2 Smart home for energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.11.3 Smart home for security . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.11.4 Smart home for health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.12 Components of Smart Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.12.1 Smart objects/Smart devices . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.12.2 Hubs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.13 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.13.1 Presentation of the sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.14 Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.15 Connecting house . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.15.1 Wireless smart home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.16 Smart home management systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.16.1 Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.16.2 Third parties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.17 Advantages and disadvantages of Smart home . . . . . . . . . . . . . . . . . . . . . 21
1.17.1 Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.17.2 Disadvantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.18 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Chapter2: SECURITY IN SMART HOME 22
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2 Fundamentals of a Secure System . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.1 Confidentiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.2 Integrity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.3 Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.4 Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.3 Types of Smart Home Security Threats and Vulnerabilities in Smart Home . . . . . . 24
2.3.1 Unintentional Threats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.2 Malfunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3.3 Intentional threats/abuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.4 Strategies for Mitigating Security Attacks in Smart Home Systems . . . . . . . . . . 27
2.4.1 Fighting against phishing . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.2 Malicious code detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.3 Tamper resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.4 Security against eavesdropping . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.5 Snifng detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.6 Network monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.7 Secure key management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.8 Physical protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5 Strong Security Protocols and Best Practices for Smart Home systems . . . . . . . . 29
2.5.1 Network Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.2 Strong Authentication Methods . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.3 Encryption Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.4 Regular Security Audits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.5 Device Firmware Integrity Verification . . . . . . . . . . . . . . . . . . . . 30
2.5.6 Intrusion Detection Systems (IDS) . . . . . . . . . . . . . . . . . . . . . . . 30
2.5.7 Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.6 Standards and Regulations for smarthome . . . . . . . . . . . . . . . . . . . . . . . 31
..........Côte titre : MAI/0852 Enhancing IoT Security For Smart Homes Through blockchain [texte imprimé] / Hichem Maazouz, Auteur ; Haithem Berhail ; Goudjil, Lakhdar, Directeur de thèse . - [S.l.] : Setif:UFA, 2024 . - 1 vol (80 f .) ; 29 cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique
Enhancing IoT SecurityIndex. décimale : 004 - Informatique Résumé :
Integrating Internet of Things (IoT) technology into smart homes significantly advances home automation
and security. However, the proliferation of IoT devices introduces complex security vulnerabilities.
Blockchain technology, with its decentralized and secure nature, offers a promising solution.
This thesis introduces HomeChain, a blockchain-based security framework for smart homes, enhancing
data integrity, privacy, and access control in IoT networks. We analyze HomeChain’s architecture
and functionality and conduct a performance evaluation focusing on its effectiveness in mitigating
common smart home security threats. The results demonstrate blockchain’s potential to improve security
and operational efficiency in smart home IoT systems, positioning it as a leading candidate for
standardizing smart home security solutions.Note de contenu : Sommaire
GENERAL INTRODUCTION 1
Chapter1: IoT AND SMART HOME 2
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Architecture of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.1 Three layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.2 Five-Layer Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.3 Middle Ware Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.4 SoA Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 IoT layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 Perception layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.2 Network layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.3 Application Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Application of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.1 Smart Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.2 Healthcare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.3 Smart industrial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5.4 Smart Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6 IoT Communication Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6.1 MQTT (Message Queue Telemetry Transport) . . . . . . . . . . . . . . . . 7
1.6.2 CoAP (Constrained Application Protocol) . . . . . . . . . . . . . . . . . . . 7
1.6.3 Extensible Messaging and Presence Protocol (XMPP) . . . . . . . . . . . . 8
1.7 Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.8 Main Issues and Challenges of IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.1 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.2 Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8.3 Interoperability and standards . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.8.4 Regulatory and rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.9 Smart Home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.10 How smart home works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.11 Different areas of application of smart home . . . . . . . . . . . . . . . . . . . . . . 13
1.11.1 Smart home for comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.11.2 Smart home for energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.11.3 Smart home for security . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.11.4 Smart home for health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.12 Components of Smart Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.12.1 Smart objects/Smart devices . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.12.2 Hubs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.13 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.13.1 Presentation of the sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.14 Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.15 Connecting house . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.15.1 Wireless smart home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.16 Smart home management systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.16.1 Cloud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.16.2 Third parties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.17 Advantages and disadvantages of Smart home . . . . . . . . . . . . . . . . . . . . . 21
1.17.1 Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.17.2 Disadvantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.18 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Chapter2: SECURITY IN SMART HOME 22
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2 Fundamentals of a Secure System . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.1 Confidentiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2.2 Integrity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.3 Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.4 Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.3 Types of Smart Home Security Threats and Vulnerabilities in Smart Home . . . . . . 24
2.3.1 Unintentional Threats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.2 Malfunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3.3 Intentional threats/abuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.4 Strategies for Mitigating Security Attacks in Smart Home Systems . . . . . . . . . . 27
2.4.1 Fighting against phishing . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.2 Malicious code detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.3 Tamper resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.4 Security against eavesdropping . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.5 Snifng detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.6 Network monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.7 Secure key management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.8 Physical protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5 Strong Security Protocols and Best Practices for Smart Home systems . . . . . . . . 29
2.5.1 Network Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.2 Strong Authentication Methods . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.3 Encryption Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.4 Regular Security Audits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.5 Device Firmware Integrity Verification . . . . . . . . . . . . . . . . . . . . 30
2.5.6 Intrusion Detection Systems (IDS) . . . . . . . . . . . . . . . . . . . . . . . 30
2.5.7 Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.6 Standards and Regulations for smarthome . . . . . . . . . . . . . . . . . . . . . . . 31
..........Côte titre : MAI/0852 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0852 MAI/0852 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
Titre : "PHARMACEUTICAL SUPPLY CHAIN MANAGEMENT" Type de document : document électronique Auteurs : Ishak Kerrouche ; Goudjil, Lakhdar, Directeur de thèse Editeur : Setif:UFA Année de publication : 2024 Importance : 1 vol (66 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Inventory Management
Demand Forecasting
Counterfeit MedicinesIndex. décimale : 004 Informatique Résumé :
Effective management of inventory, demand, transportation, and quality is essential for achieving operational efficiency and maintaining product integrity within the pharmaceutical sector. This document examines fundamental principles such as cost reduction, demand forecasting, cold chain logistics, and quality control aimed at enhancing supply chain performance. A significant focus is placed on addressing the issue of counterfeit medications through the implementation of Good Supply Chain Practices (GSCP) and advanced traceability technologies. For platforms like “PharmaConnect,” these strategies are critical for fostering collaboration among pharmacies, manufacturers, and distributors, ensuring the prompt delivery of genuine medicines, and upholding regulatory standards. By utilizing innovative solutions and strong management practices, “PharmaConnect” contributes to public health and improves industry efficiency.Note de contenu :
Sommaire
GENERAL INTRODUCTION………………………………………………………..…1
Theoretical part
Chapter I. Stock management
I.1. Introduction……………………………………………………………………...……3
I.2. Definition of stock management………………………………….……...…...4
I.3. Principles of stock management………………………………………………..…5
I.4. Stock management methods………………………………………………………………5
I.4.1. FIFO method (First in, First Out)……………….…………………………………6
I.4.2. LIFO Method (Last in, First Out)………………………………………………….6
I.4.3. Weighted average cost method………………………………..…………………...6
I.4.4. ABC analysis………………………………………………………………….…...7
I.4.5. Computerized inventory management systems……………….……………….…..7
I.5. Optimization of stock levels…………………………………………..……………….…..9
I.6. Management of pharmaceutical products………….………………...……….…11
I.6.1. Temperature control………………………………….…...………………………11
I.6.2. Management of expiration dates……………………………………………….…11
I.6.3. Regulatory conformity…………………………………….…...………………....11
I.6.4. Product traceability………………………………………….……………………11
I.6.5. Orders and supplies management………………………….……………………..11
I.6.6. Security and confidentiality…………………………………..…………………..12
I.7. Conclusion ……………………………………………………………………………..….13
Chapter II. Demand planning
II.1.Introduction………………………………………………………………….…………...14
II.2. Definition of demand planning………………..………………………..……….15
II.3. Forecasting of the demand for drugs……………………..………….…….……16
II.34 Factors influencing the demand for drugs…………………….……….……….17
II.4.1. Demography……………………………………………………………………..17
II.4.2. Epidemiology and Public Health……………………………….………………..18
II.4.3. Medical and technological advances……………………..……….…….……….18
II.4.4. Health policies and regulations .…………………………………...……………18
II.4.5. Consumer behavior and health professionals……………………….………….18
II.5. demand planning methods………………………………………….….………19
II.5.1. Quantitative forecasts……………………..…………...……………………….19
II.5.2. Qualitative Forecasting…………………….……………………….…………. 21
II.6. Demand Management Strategies……………………………..…………….………….22
II.7. Conclusion…………………………………………………………..……….…………..24
Chapter III. Transport and Logistics
III.1. Introduction…………………………………………………………….…………..…..25
III.2. Definition of Transportation and Logistics………………………………...….26
III.3. Transportation of Pharmaceuticals……………………………….........……..26
III.4. Cold Chain Requirements…………………………...…………………………………28
III.5. Pharmaceutical Logistics……………………………………………...………..29
III.6. Safety Stock Management………………………………………………………30
III.7. Conclusion…………………………………………………………………..…………………32
Chapter IV. Quality Management
IV.1. Introduction…………………………………………………………..………………....33
IV.2. Definition of Quality Management …………………………………………… 34
IV.3. Good Manufacturing Practices (GMP) …………………..………..…………35
IV.4. Good Distribution Practices (GDP)…………………………………….………36
IV.5. Quality Management System (QMS)…………………..………….…………..38
IV.6. Quality control of medicinal products…………………………………...……..41
IV.7. Conclusion…………………………………………………………………..…….……..43
Chapter V. Fight against counterfeiting
V.1. Introduction…………………………………………………….……….………………..44
V.2. Definition of anti-counterfeiting……………………………………….………...45
V.3. Anti-counterfeiting efforts…………………………………………..…..……….45
V.4. Scope of the problem of counterfeit medicines………..………..………………46
V.5. Risks Associated with Counterfeit Medicines……………...….………………..47
V.6. Anti-counterfeiting strategies……………………………………………………48
V.7. Role of GSCP in the fight against counterfeiting…………….……..………….50
V.8. Conclusion………………………………………………………………………...……...52
Chapter VI. PRACTICAL PART
PharmaConnect Technical Specifications…………………………..……………………….53
VI.1. Overview………………………………………………………………………...53
VI.2.1. Technologies…………………………………………………………………...53
VI.2.2. Features……………………………………………………………...…………53
VI.3. Frontend…………………………………………………………………………54
VI.3.1. Technologies………………………………………………..………….………54
VI.3.2. Features……………………………………………………...…………………54
VI.4. Security…………………………………………………………………………..54
VI.4.1. Authentication and Authorization………………………...……………………54
VI.5. Documentation…….......………………………………………………………..55
VI.5.1. API Documentation………………..........................………………………………..55
the start-up projects
FIRST AXIS Presentation of the start-up project
I. Presentation of the project………………………………………………….………………56
I.1. The project idea (proposed solution)…………………………………….…………56
I.2. The proposed values…………………………………………………………...……56
I.3. Teamwork ……………………………………...…..…………………………….....57
I.4. The project’s objectives………………………………..……………..……………..57
I.5. Completion schedule…………………………………….……………..……………58
SECOND AXIS Innovative aspects
II. Innovative aspects………………………………………….…………………………….59
II.1. The nature of the innovation……….…………………..……………………59
II.2. The field of innovation…………………..…………………..………………..59
THIRD AXIS Strategic market analysis
III. Strategic market analysis…………………………….…...……………………………60
III.1. The market segments………………………….………………..…….……..60
III.2. The intensity of competition for this project..……………………………..60
III.3. Project marketing strategy………………………….………………………61
FOURTH AXIS Production and Organization plan
IV. Production and organization plan………………….……………………..……………….62
IV.1. Procurement……………………………………….………………..…………………62
IV.2. Workforce (employees)………………………………..………….…………………..62
IV.3. The Main Partners……………………………………..………..…..………………62
FIFTH AXIS Financial plan
V. Financial Plan………………………………………………….……..…………………..64
V.1. Costs and expenses………………………………………………..……………………64Côte titre : MAI/0960 "PHARMACEUTICAL SUPPLY CHAIN MANAGEMENT" [document électronique] / Ishak Kerrouche ; Goudjil, Lakhdar, Directeur de thèse . - [S.l.] : Setif:UFA, 2024 . - 1 vol (66 f .) ; 29 cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Inventory Management
Demand Forecasting
Counterfeit MedicinesIndex. décimale : 004 Informatique Résumé :
Effective management of inventory, demand, transportation, and quality is essential for achieving operational efficiency and maintaining product integrity within the pharmaceutical sector. This document examines fundamental principles such as cost reduction, demand forecasting, cold chain logistics, and quality control aimed at enhancing supply chain performance. A significant focus is placed on addressing the issue of counterfeit medications through the implementation of Good Supply Chain Practices (GSCP) and advanced traceability technologies. For platforms like “PharmaConnect,” these strategies are critical for fostering collaboration among pharmacies, manufacturers, and distributors, ensuring the prompt delivery of genuine medicines, and upholding regulatory standards. By utilizing innovative solutions and strong management practices, “PharmaConnect” contributes to public health and improves industry efficiency.Note de contenu :
Sommaire
GENERAL INTRODUCTION………………………………………………………..…1
Theoretical part
Chapter I. Stock management
I.1. Introduction……………………………………………………………………...……3
I.2. Definition of stock management………………………………….……...…...4
I.3. Principles of stock management………………………………………………..…5
I.4. Stock management methods………………………………………………………………5
I.4.1. FIFO method (First in, First Out)……………….…………………………………6
I.4.2. LIFO Method (Last in, First Out)………………………………………………….6
I.4.3. Weighted average cost method………………………………..…………………...6
I.4.4. ABC analysis………………………………………………………………….…...7
I.4.5. Computerized inventory management systems……………….……………….…..7
I.5. Optimization of stock levels…………………………………………..……………….…..9
I.6. Management of pharmaceutical products………….………………...……….…11
I.6.1. Temperature control………………………………….…...………………………11
I.6.2. Management of expiration dates……………………………………………….…11
I.6.3. Regulatory conformity…………………………………….…...………………....11
I.6.4. Product traceability………………………………………….……………………11
I.6.5. Orders and supplies management………………………….……………………..11
I.6.6. Security and confidentiality…………………………………..…………………..12
I.7. Conclusion ……………………………………………………………………………..….13
Chapter II. Demand planning
II.1.Introduction………………………………………………………………….…………...14
II.2. Definition of demand planning………………..………………………..……….15
II.3. Forecasting of the demand for drugs……………………..………….…….……16
II.34 Factors influencing the demand for drugs…………………….……….……….17
II.4.1. Demography……………………………………………………………………..17
II.4.2. Epidemiology and Public Health……………………………….………………..18
II.4.3. Medical and technological advances……………………..……….…….……….18
II.4.4. Health policies and regulations .…………………………………...……………18
II.4.5. Consumer behavior and health professionals……………………….………….18
II.5. demand planning methods………………………………………….….………19
II.5.1. Quantitative forecasts……………………..…………...……………………….19
II.5.2. Qualitative Forecasting…………………….……………………….…………. 21
II.6. Demand Management Strategies……………………………..…………….………….22
II.7. Conclusion…………………………………………………………..……….…………..24
Chapter III. Transport and Logistics
III.1. Introduction…………………………………………………………….…………..…..25
III.2. Definition of Transportation and Logistics………………………………...….26
III.3. Transportation of Pharmaceuticals……………………………….........……..26
III.4. Cold Chain Requirements…………………………...…………………………………28
III.5. Pharmaceutical Logistics……………………………………………...………..29
III.6. Safety Stock Management………………………………………………………30
III.7. Conclusion…………………………………………………………………..…………………32
Chapter IV. Quality Management
IV.1. Introduction…………………………………………………………..………………....33
IV.2. Definition of Quality Management …………………………………………… 34
IV.3. Good Manufacturing Practices (GMP) …………………..………..…………35
IV.4. Good Distribution Practices (GDP)…………………………………….………36
IV.5. Quality Management System (QMS)…………………..………….…………..38
IV.6. Quality control of medicinal products…………………………………...……..41
IV.7. Conclusion…………………………………………………………………..…….……..43
Chapter V. Fight against counterfeiting
V.1. Introduction…………………………………………………….……….………………..44
V.2. Definition of anti-counterfeiting……………………………………….………...45
V.3. Anti-counterfeiting efforts…………………………………………..…..……….45
V.4. Scope of the problem of counterfeit medicines………..………..………………46
V.5. Risks Associated with Counterfeit Medicines……………...….………………..47
V.6. Anti-counterfeiting strategies……………………………………………………48
V.7. Role of GSCP in the fight against counterfeiting…………….……..………….50
V.8. Conclusion………………………………………………………………………...……...52
Chapter VI. PRACTICAL PART
PharmaConnect Technical Specifications…………………………..……………………….53
VI.1. Overview………………………………………………………………………...53
VI.2.1. Technologies…………………………………………………………………...53
VI.2.2. Features……………………………………………………………...…………53
VI.3. Frontend…………………………………………………………………………54
VI.3.1. Technologies………………………………………………..………….………54
VI.3.2. Features……………………………………………………...…………………54
VI.4. Security…………………………………………………………………………..54
VI.4.1. Authentication and Authorization………………………...……………………54
VI.5. Documentation…….......………………………………………………………..55
VI.5.1. API Documentation………………..........................………………………………..55
the start-up projects
FIRST AXIS Presentation of the start-up project
I. Presentation of the project………………………………………………….………………56
I.1. The project idea (proposed solution)…………………………………….…………56
I.2. The proposed values…………………………………………………………...……56
I.3. Teamwork ……………………………………...…..…………………………….....57
I.4. The project’s objectives………………………………..……………..……………..57
I.5. Completion schedule…………………………………….……………..……………58
SECOND AXIS Innovative aspects
II. Innovative aspects………………………………………….…………………………….59
II.1. The nature of the innovation……….…………………..……………………59
II.2. The field of innovation…………………..…………………..………………..59
THIRD AXIS Strategic market analysis
III. Strategic market analysis…………………………….…...……………………………60
III.1. The market segments………………………….………………..…….……..60
III.2. The intensity of competition for this project..……………………………..60
III.3. Project marketing strategy………………………….………………………61
FOURTH AXIS Production and Organization plan
IV. Production and organization plan………………….……………………..……………….62
IV.1. Procurement……………………………………….………………..…………………62
IV.2. Workforce (employees)………………………………..………….…………………..62
IV.3. The Main Partners……………………………………..………..…..………………62
FIFTH AXIS Financial plan
V. Financial Plan………………………………………………….……..…………………..64
V.1. Costs and expenses………………………………………………..……………………64Côte titre : MAI/0960 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0960 MAI/0960 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible
Titre : Un protocole MAC Asynchrone pour les Réseaux de Capteur Sans Fil Type de document : texte imprimé Auteurs : Laib,Nadhira, Auteur ; Goudjil, Lakhdar, Directeur de thèse Editeur : Setif:UFA Année de publication : 2020 Importance : 1 vol (63 f .) Format : 29 cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Réseaux de capteurs sans fil (RCSF)
Protocoles MAC Asynchrone
Duty cycle
Transmission initiée par le récepteur
Economie d’énergieIndex. décimale : 004 - Informatique Résumé :
Les réseaux de capteurs sans fil sont utilisés dans de nombreuses applications. Dans ces applications,
les noeuds capteurs disposent d’une quantité limitée d’énergie, mais doivent fonctionner
pendant des années sans avoir leurs batteries changées. Dans notre travail, nous nous intéressons
à la couche MAC afin de partager le canal équitablement et efficacement mais surtout
en minimisant la consommation d’énergie en évitant les principales causes de consommation
d’énergie : l’overhearing, l’overmiting et les fréquentes transitions entre les modes "en veille"
et "activité". Plusieurs classes de protocoles MAC pour les RCSF proposés dans la littérature,
Les protocoles MAC avec contention particulièrement les protocoles asynchrone sont des protocoles
initier par l’émetteurs ou des protocoles initier par le récepteur. Dans les MAC initiés par
le récepteur, la transmission de paquets est déclenchée par les noeuds récepteurs. Les protocoles
(MAC) duty cycle asynchrone initié par le récepteur ont démontré leur efficacité à travers diverses
études. Nous avons proposé dans ce mémoire un protocole MAC asynchrone initier par
le récepteur pour les réseaux de capteurs sans fil, appelé short frame identifier receiver initiated
(SFIRI-MAC), basés sur la contention avec un mécanisme duty cycle afin d’optimiser l’énergie.
Nous évaluons les performances du SFIRI-MAC dans le simulateur de réseau ns-2, et les résultats
de la simulation montrent que le SFIRI-MAC atteint une efficacité énergétique supérieure,
et minimise le débit réseau et le délai de bout-en-bout de délivrance de paquets.Côte titre : MAI/0366 En ligne : https://drive.google.com/file/d/1iKPNyRpd-_BDVMU_GZoJsHuXgfy5EWVG/view?usp=shari [...] Format de la ressource électronique : Un protocole MAC Asynchrone pour les Réseaux de Capteur Sans Fil [texte imprimé] / Laib,Nadhira, Auteur ; Goudjil, Lakhdar, Directeur de thèse . - [S.l.] : Setif:UFA, 2020 . - 1 vol (63 f .) ; 29 cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Réseaux de capteurs sans fil (RCSF)
Protocoles MAC Asynchrone
Duty cycle
Transmission initiée par le récepteur
Economie d’énergieIndex. décimale : 004 - Informatique Résumé :
Les réseaux de capteurs sans fil sont utilisés dans de nombreuses applications. Dans ces applications,
les noeuds capteurs disposent d’une quantité limitée d’énergie, mais doivent fonctionner
pendant des années sans avoir leurs batteries changées. Dans notre travail, nous nous intéressons
à la couche MAC afin de partager le canal équitablement et efficacement mais surtout
en minimisant la consommation d’énergie en évitant les principales causes de consommation
d’énergie : l’overhearing, l’overmiting et les fréquentes transitions entre les modes "en veille"
et "activité". Plusieurs classes de protocoles MAC pour les RCSF proposés dans la littérature,
Les protocoles MAC avec contention particulièrement les protocoles asynchrone sont des protocoles
initier par l’émetteurs ou des protocoles initier par le récepteur. Dans les MAC initiés par
le récepteur, la transmission de paquets est déclenchée par les noeuds récepteurs. Les protocoles
(MAC) duty cycle asynchrone initié par le récepteur ont démontré leur efficacité à travers diverses
études. Nous avons proposé dans ce mémoire un protocole MAC asynchrone initier par
le récepteur pour les réseaux de capteurs sans fil, appelé short frame identifier receiver initiated
(SFIRI-MAC), basés sur la contention avec un mécanisme duty cycle afin d’optimiser l’énergie.
Nous évaluons les performances du SFIRI-MAC dans le simulateur de réseau ns-2, et les résultats
de la simulation montrent que le SFIRI-MAC atteint une efficacité énergétique supérieure,
et minimise le débit réseau et le délai de bout-en-bout de délivrance de paquets.Côte titre : MAI/0366 En ligne : https://drive.google.com/file/d/1iKPNyRpd-_BDVMU_GZoJsHuXgfy5EWVG/view?usp=shari [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0366 MAI/0366 Mémoire Bibliothéque des sciences Français Disponible
Disponible
Permalink
Permalink
PermalinkPermalinkPermalink
