Intelligent Security Management and Control in the IoT

The Internet of Things (IoT) has contributed greatly to the growth of data traffic on the Internet. Access technologies and object constraints associated with the IoT can cause performance and security problems. This relates to important challenges such as the control of radio communications and network access, the management of service quality and energy consumption, and the implementation of security mechanisms dedicated to the IoT. In response to these issues, this book presents new solutions for the management and control of performance and security in the IoT. The originality of these proposals lies mainly in the use of intelligent techniques. This notion of intelligence allows, among other things, the support of object heterogeneity and limited capacities as well as the vast dynamics characterizing the IoT.

Table of Contents:
Chapter 1 Multicriteria Selection of Transmission Parameters in the IoT 1 Sinda BOUSSEN, Mohamed-Aymen CHALOUF and Francine KRIEF 1.1 Introduction 1 1.2 Changing access network in the IoT 2 1.3 Spectrum handoff in the IoT 3 1.4 Multicriteria decision-making module for an effective spectrum handoff in the IoT 4 1.4.1 General architecture 4 1.4.2 Decision-making flowchart 9 1.4.3 Performances evaluation 15 1.5 Conclusion 22 1.6 References 22 Chapter 2 Using Reinforcement Learning to Manage Massive Access in NB-IoT Networks 27 Yassine HADJADJ-AOUL and Soraya AIT-CHELLOUCHE 2.1 Introduction 27 2.2 Fundamentals of the NB-IoT standard 29 2.2.1 Deployment and instances of use 29 2.2.2 Transmission principles 30 2.2.3 Radio resource random access procedure 33 2.3 State of the art 37 2.4 Model for accessing IoT terminals 39 2.5 Access controller for IoT terminals based on reinforcement learning 42 2.5.1 Formulating the problem 42 2.5.2 Regulation system for arrivals 44 2.6 Performance evaluation 46 2.7 Conclusion 51 2.8 References 51 Chapter 3 Optimizing Performances in the IoT: An Approach Based on Intelligent Radio 57 Badr BENMAMMAR 3.1 Introduction 57 3.2 Internet of Things (IoT) 58 3.2.1 Definition of the IoT 58 3.2.2 Applications of the IoT 59 3.2.3 IoT challenges 60 3.2.4 Enabling technologies in the IoT 61 3.3 Intelligent radio 64 3.3.1 Definition of intelligent radio 64 3.3.2 Motivations for using intelligent radio in the IoT 66 3.3.3 Challenges in using intelligent radio in the IoT 68 3.4 Conclusion 71 3.5 References 73 Chapter 4 Optimizing the Energy Consumption of IoT Devices 77 Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 4.1 Introduction 77 4.2 Energy optimization 78 4.2.1 Definitions 78 4.3 Optimization techniques for energy consumption 79 4.3.1 The A* algorithm 79 4.3.2 Fuzzy logic 80 4.4 Energy optimization in the IoT 82 4.4.1 Characteristics of the IoT 82 4.4.2 Challenges in energy optimization 84 4.4.3 Research on energy optimization in the IoT 84 4.5 Autonomous energy optimization framework in the IoT 86 4.5.1 Autonomous computing 86 4.5.2 Framework specification 89 4.6 Proposition of a self-optimization method for energy consumption in the IoT 90 4.6.1 Fuzzy logic model 91 4.6.2 Decision-making algorithm 95 4.6.3 Evaluating energy self-optimization in the IoT 97 4.7 Conclusion 101 4.8 References 101 Chapter 5 Toward Intelligent Management of Service Quality in the IoT: The Case of a Low Rate WPAN 105 Guillaume LE GALL, Georgios Z PAPADOPOULOS, Mohamed-Aymen CHALOUF and Olivier TOGNI 5.1 Introduction 106 5.2 Quick overview of the IoT 108 5.2.1 The micro-IPv6 stack 108 5.2.2 Technologies for the IoT 110 5.2.3 IoT and quality of service 114 5.3 IEEE 802.15.4 TSCH approach 115 5.4 Transmission scheduling 117 5.4.1 General considerations 117 5.4.2 Scheduling in the literature 118 5.5 Routing and RPL 120 5.5.1 Routing 120 5.5.2 RPL 121 5.5.3 Multipath 122 5.6 Combined approach based on 802.15.4 TSCH and multipath RPL 123 5.6.1 Automatic Repeat reQuest 125 5.6.2 Replication and Elimination 125 5.6.3 Overhearing 127 5.7 Conclusion 127 5.8 References 128 Chapter 6 Adapting Quality of Service of Energy-Harvesting IoT Devices 133 Matthieu GAUTIER and Olivier BERDER 6.1 Toward the energy autonomy of sensor networks 135 6.1.1 Energy harvesting and management 135 6.1.2 State-of-the-art energy managers 138 6.2 Fuzzyman: use of fuzzy logic 141 6.2.1 Design of Fuzzyman 141 6.2.2 Evaluating Fuzzyman 145 6.2.3 Conclusion 146 6.3 RLMan: using reinforcement learning 148 6.3.1 Formulating the problem of managing the harvested energy 148 6.3.2 RLMan algorithm 150 6.3.3 Evaluation of RLMan 153 6.3.4 Conclusion 155 6.4 Toward energy autonomous LoRa nodes 155 6.4.1 Multisource energy-harvesting architecture 157 6.4.2 Applying energy management to LoRa nodes 157 6.5 Conclusion 157 6.6 References 160 Chapter 7 Adapting Access Control for IoT Security 163 Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 7.1 Introduction 163 7.2 Defining security services in the IoT 164 7.2.1 Identification and authentication in the IoT 164 7.2.2 Access control in the IoT 165 7.2.3 Confidentiality in the IoT 166 7.2.4 Integrity in the IoT 166 7.2.5 Non-repudiation in the IoT 167 7.2.6 Availability in the IoT 167 7.3 Access control technologies 168 7.4 Access control in the IoT 172 7.4.1 Research on the extension of access control models for the IoT 172 7.4.2 Research on adapting access control systems and technologies for the IoT 173 7.5 Access control framework in the IoT 176 7.5.1 IoT architecture 177 7.5.2 IoT-MAAC access control specification 179 7.6 Conclusion 193 7.7 References 194 Chapter 8 The Contributions of Biometrics and Artificial Intelligence in Securing the IoT 197 Amal SAMMOUD, Omessaad HAMDI, Mohamed-Aymen CHALOUF and Nicolas MONTAVONT 8.1 Introduction 197 8.2 Security and privacy in the IoT 198 8.3 Authentication based on biometrics 199 8.3.1 Biometrics 199 8.3.2 Biometric techniques 199 8.3.3 The different properties of biometrics 200 8.3.4 Operating a biometric system 201 8.3.5 System performances 202 8.4 Multifactor authentication techniques based on biometrics 202 8.4.1 Multifactor authentication 203 8.4.2 Examples of multifactor authentication approaches for securing the IoT 204 8.4.3 Presentation of the approach of Sammoud et al (2020c) 205 8.5 Authentication techniques based on biometrics and machine learning 213 8.5.1 Machine learning algorithms 213 8.5.2 Examples of authentication approaches based on biometrics and machine learning 214 8.5.3 Authentication approaches based on ECG and machine learning 215 8.6 Challenges and limits 217 8.6.1 Quality of biometric data 217 8.6.2 Non-revocability of biometric data 218 8.6.3 Security of biometric systems 218 8.7 Conclusion 218 8.8 References 218 Chapter 9 Dynamic Identity and Access Management in the IoT: Blockchain-based Approach 223 Léo MENDIBOURE, Mohamed-Aymen CHALOUF and Francine KRIEF 9.1 Introduction 223 9.2 Context 224 9.2.1 Intelligent identity and access management 225 9.2.2 Blockchain 226 9.3 Blockchain for intelligent identity and access management 227 9.3.1 A new architecture integrating blockchain 228 9.3.2 The different benefits 229 9.4 Challenges 234 9.4.1 Scaling up 235 9.4.2 Blockchain security 235 9.4.3 Energy consumption 236 9.4.4 Definition of consensus algorithms based on artificial intelligence 236 9.5 Conclusion 237 9.6 References 237 Chapter 10 Adapting the Security Level of IoT Applications 243 Tidiane SYLLA, Mohamed-Aymen CHALOUF and Francine KRIEF 10.1 Introduction 243 10.2 Definitions and characteristics 244 10.2.1 Definitions 244 10.2.2 Characteristics 244 10.3 IoT applications 246 10.4 IoT architectures 246 10.5 Security, trust and privacy protection in IoT applications 247 10.5.1 General remarks 248 10.5.2 Security services 248 10.5.3 Communication security 251 10.5.4 Trust 252 10.5.5 Privacy 253 10.6 Adapting the security level in the IoT 254 10.6.1 Context-awareness 255 10.6.2 Context-aware security 256 10.6.3 Context-aware security architecture and privacy protection designed using the “as a service” approach 258 10.7 Conclusion 261 10.8 References 261 Chapter 11 Moving Target Defense Techniques for the IoT 267 Renzo E NAVAS, Laurent TOUTAIN and Georgios Z PAPADOPOULOS 11.1 Introduction 268 11.2 Background 269 11.2.1 Brief chronology of Moving Target Defense 269 11.2.2 Fundamental technical and taxonomic principles of MTD 270 11.3 Related works 271 11.3.1 Surveys on MTD techniques 271 11.3.2 Frameworks for IoT systems linked to the concept of MTD 271 11.4 LMTD for the IoT: a qualitative survey 272 11.4.1 Data: MTD mechanism against side-channel channel attacks based on renegotiating cryptographic keys 272 11.4.2 Software 272 11.4.3 Runtime environment 273 11.4.4 Platform: diversifying by reconfiguring the IoT node firmware 275 11.4.5 Networks 275 11.4.6 Section summary 278 11.5 Network components in the IoT: a vast domain for MTD 279 11.5.1 Physical layer 280 11.5.2 Link layer 281 11.5.3 OSI network layer 281 11.5.4 Transport layer 282 11.5.5 Application layer 283 11.5.6 Section summary 284 11.6 An MTD framework for the IoT 284 11.6.1 Proposition: components 284 11.6.2 Instantiation: UDP port hopping 286 11.7 Discussion and avenues for future research 287 11.8 Conclusion 288 11.9 References 288 List of Authors 293 Index 295

About the Author :
Mohamed-Aymen Chalouf is Associate Professor of Computer Science at the University of Rennes 1 (IUT Lannion), France. He is also a member of the OCIF team (Communicating Objects for the Internet of the Future) at IRISA Laboratory.