Design Frameworks for Wireless Networks (eBook)
XXI, 433 Seiten
Springer Singapore (Verlag)
978-981-13-9574-1 (ISBN)
Dr. Santosh Kumar Das received his Ph.D. degree in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India, in 2018 and completed his M. Tech. degree in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology (erstwhile WBUT), West Bengal, India, in 2013. He is currently working as Assistant Professor at School of Computer Science & Engineering, National Institute of Science and Technology, Berhampur, Odisha-761008. He is having more than eight years teaching experience. He has contributed more than 25 research papers. His research interests mainly focus on Ad-hoc and Sensor Network, Artificial Intelligence, Soft Computing, and Mathematical modeling.
This book provides an overview of the current state of the art in wireless networks around the globe, focusing on utilizing the latest artificial intelligence and soft computing techniques to provide design frameworks for wireless networks. These techniques play a vital role in developing a more robust algorithm suitable for the dynamic and heterogeneous environment, making the network self-managed, self-operational, and self-configurational, and efficiently reducing uncertainties and imprecise information.
Foreword 6
Preface 9
Objective of the Book 9
Organization of the Book 10
List of Reviewers 15
Contents 17
About the Editors 19
Design and Enhancement of Security and Privacy Technique 22
An Analysis and Comparison of Security Protocols on Wireless Sensor Networks (WSN) 23
1 Introduction 24
2 Literature Survey 25
3 Security in Wireless Sensor Networks (WSN) 26
3.1 Sanctuary Requirements in WSN 26
3.2 Constraints in WSN 27
3.3 Security Threat Models 28
3.4 Security Solutions in WSN 32
4 Key Management Systems 33
4.1 Protocols and Methods Classification 34
5 Analysis and Discussion 37
5.1 Analysis Method 37
5.2 Discussion 38
6 Conclusions 39
References 39
On the Security Weaknesses in Password-Based Anonymous Authentication Scheme for E-Health Care 42
1 Introduction 43
1.1 Threat Model 44
1.2 Bio-hash Function 44
1.3 Contribution 45
1.4 Organization of This Article 45
2 Literature Review 46
3 Overview of Mishra et al. mishra:bar Protocol 47
3.1 Registration Phase 47
3.2 Login Phase 48
3.3 Verification Phase 50
3.4 Password Change Phase 50
3.5 Smart Card Revocation Phase 51
4 Cryptanalysis of Mishra et al. mishra:bar Scheme 51
4.1 Designing Imperfection in Login Phase 51
4.2 Designing Imperfection in Authentication Phase 51
4.3 Designing Imperfection in Password Change Phase 52
4.4 Lack of Biometric Update or Change Phase 53
4.5 Strong Replay Attack 53
4.6 Clock Synchronization Problem 53
5 Performance Comparison 54
6 Future Scope 57
7 Conclusion 57
References 57
Integrated Probabilistic Relevancy Classification (PRC) Scheme for Intrusion Detection in SCADA Network 60
1 Introduction 61
2 Related Work 63
3 Proposed Method 66
3.1 Preprocessing 69
3.2 String Matching 71
3.3 Clustering and Classification 71
4 Performance Analysis 74
4.1 Confusion Matrix 75
4.2 Error Rate 76
4.3 Recall 76
4.4 False Detection Rate 77
4.5 Classification Result for Existing and Proposed Classifiers 78
4.6 Sensitivity, Specificity, and Accuracy 78
5 Conclusion 81
References 81
Intrusion Detection System in Internet of Things 83
1 Introduction 84
2 Motivation 84
3 Internet of Thing 85
3.1 IoT Architecture 85
3.2 Life Cycle of IoT and Possible Attacks 86
4 Comparison of Internet of Things and Traditional IP Network 88
4.1 IoT Protocol Stack 88
4.2 IPv6 Border Router (6BR) 90
5 Intrusion Detection System 90
5.1 Intrusion Detection Approaches 91
6 Cyberattacks in IoT Applications 92
6.1 Wormhole Attack 93
6.2 Sinkhole Attack 93
6.3 Selective Forwarding Attack 94
6.4 Sybil Attack and Clone ID Attack 94
6.5 Hello Flood Attack 94
6.6 Denial of Service (DOS) Attack 94
7 Security in IoT Applications 95
7.1 IPSec Capabilities in IoT System 95
7.2 Challenges and Design Criteria of IoT Security System 96
7.3 Need of IDSs in IoT 96
8 Intrusion Detection System in IoT Applications 97
8.1 Intrusion Detection System for Dos Attack 97
8.2 Intrusion Detection System for Wormhole Attack 100
8.3 Intrusion Detection System for Sinkhole Attack 102
8.4 Intrusion Detection System for Internet of Things 104
8.5 Comparative Analysis of SVELTE and INTI IDSs 108
9 Conclusion 109
References 110
Deep Learning and Machine Learning Techniques for Intrusion Detection and Prevention in Wireless Sensor Networks: Comparative Study and Performance Analysis 112
1 Introduction 113
2 Literature Survey 113
3 Proposed Methodology 115
4 Comparative Analysis and Discussions 116
4.1 Support Vector Machine 119
4.2 Naïve Bayes 122
4.3 Random Forest 124
4.4 Decision Tree 126
4.5 K-Nearest Neighbor 129
5 Deep Learning Approach 131
6 Conclusion 133
References 135
Design of Automation and Troubleshooting Technique 138
Study and Design of Route Repairing Mechanism in MANET 139
1 Introduction 140
2 Related Work 141
3 Proposed Work 146
3.1 Route Discovery 147
3.2 Route Recovery 148
4 Simulation Results and Analysis 157
4.1 Packet Delivery Ratio 160
4.2 End-to-End Delay 161
4.3 Packet Loss 161
5 Conclusion 163
References 163
A Comprehensive Parameterized Resource Allocation Approach for Wireless Sensor Networks 166
1 Introduction 167
1.1 Background of Wireless Sensor Network 169
1.2 Features of Wireless Sensor Networks 171
1.3 Challenges and Constraints 172
1.4 Energy 172
1.5 Congestion 173
1.6 Node Deployment 173
1.7 Wireless Medium 174
1.8 Hardware Constraints 174
1.9 Security 175
2 Related Work 176
3 System Model and Problem Statement 181
4 Algorithm Design: CPRA 182
5 Performance Evaluation 185
5.1 Parameters for Performance Evaluation 186
6 Conclusion 188
References 189
Effect of Wormhole Attacks on MANET 191
1 Introduction 192
2 Related Works 193
3 Characteristics of MANET 194
3.1 Ins and Outs of MANET 194
3.2 Working Principal of MANET 195
3.3 Commonly Used Terms in AODV Ecosystem 196
4 Problem Formulation 197
5 Wormhole Attack 197
5.1 Attack Medium 198
5.2 Attacking Modes 200
5.3 Effects of the Attack 200
6 Simulation Environment 201
6.1 Attack Simulation 202
7 Conclusion 207
References 208
Distributed Online Fault Diagnosis in Wireless Sensor Networks 210
1 Introduction 210
2 Faults, Errors, and Failures in Sensor Networks 212
3 Related Work 213
4 System Model 215
4.1 Assumptions, Notations, and Their Meanings 215
4.2 Network Model 216
4.3 Fault Model 217
5 Data Modeling and Problem Formulation 218
5.1 Data Model 219
5.2 Problem Formulation 220
6 Distributed Intermittent Self Fault Diagnosis Algorithm 220
7 Analysis of the Distributed Fault Diagnosis Algorithm 221
7.1 Data Analysis of an Intermittent Faulty Sensor 221
7.2 Mathematical Analysis of the Distributed Fault Diagnosis Algorithm 224
8 Result and Discussion 226
8.1 Simulation Model 227
8.2 Confidence Interval 230
9 Conclusion 232
References 232
Ambient Intelligence for Patient-Centric Healthcare Delivery: Technologies, Framework, and Applications 235
1 Introduction 235
2 Supporting Technologies for Ambient Intelligence Systems 238
2.1 Sensors 238
2.2 Networks 241
2.3 Human–Computing Interface 241
2.4 Pervasive Computing 242
2.5 Artificial Intelligence 243
2.6 Software Agent 243
2.7 Internet of Things 244
3 Emergence of Ambient Intelligence in Healthcare Delivery 244
3.1 Medical Information Systems 245
3.2 Wearable Devices 246
3.3 Ambient Assisted Living (AAL) 247
3.4 Health Knowledge 247
3.5 Intelligent Diagnosis 248
3.6 Work Flow Process 248
4 Role of Wireless Body Area Networks in Healthcare AmI Systems 248
5 Patient-Centric Ambient Healthcare Framework 252
5.1 Sensing and Communication 254
5.2 Context-Aware Reasoning Engine 254
5.3 Case-Based Reasoning Engine 255
5.4 Intelligent Techniques and Data Mining Services 256
5.5 Cloud Server Storage and Data Management 256
5.6 Sensory Data Fusion Using Markov Chain Model 257
5.7 Web Services Module 258
6 Major Applications of AmI in Healthcare 259
6.1 Uninterrupted Health Status Monitoring 259
6.2 Activity Recognition 260
6.3 Human Stress and Energy Expenditure Assessment 260
7 Illustration Case—Ambient Assisted Care (AAC) at Hospital 260
8 Conclusion and Future Scope 263
References 264
Design of Optimization Based Network Lifetime Enhancement Technique 267
Evolutionary Algorithms for Coverage and Connectivity Problems in Wireless Sensor Networks: A Study 268
1 Introduction 268
2 Sensing and Communication Model 270
2.1 Binary Sensing Model 270
2.2 Probabilistic Sensing Model 270
2.3 Communication Model 271
3 Coverage and Connectivity 271
3.1 Coverage 271
3.2 Connectivity 273
4 Evolutionary Algorithms for Coverage and Connectivity 273
4.1 Genetic Algorithm 274
4.2 Harmony Search Algorithm 278
4.3 Ant Colony Optimization 280
4.4 Non-dominated Sorting Genetic Algorithm (NSGA–II) 283
4.5 Some Other Evolutionary Algorithms 285
5 Research Challenges and Open Issues 286
5.1 Optimum Node Deployment 286
5.2 Three-Dimensional Networks 286
5.3 Lifetime Maximization of Networks 286
5.4 Fault Tolerance 287
5.5 Real-Time Protocols 287
5.6 Nonuniformity in Sensing and Communication Range 287
5.7 Coverage and Connectivity in Presence of Obstacles 287
6 Conclusion 288
References 288
Nature-Inspired Algorithms for k-Coverage and m-Connectivity Problems in Wireless Sensor Networks 292
1 Introduction 293
1.1 Author’s Contribution 294
1.2 Organization of the Chapter 295
2 Nature-Inspired Algorithms 295
2.1 Genetic Algorithm 295
2.2 Particle Swarm Optimization 296
2.3 Differential Evolution 296
2.4 Gravitational Search Algorithm 297
3 Network Model and Problem Formulation 299
3.1 Network Model 299
3.2 Terminologies 299
3.3 Problem Definition 300
3.4 Derivation of Fitness Function 301
4 GA-Based Approach 302
4.1 Chromosome Encoding 302
4.2 Initialization of Population 303
4.3 Fitness Function 303
4.4 Selection, Crossover, and Mutation Operation 303
5 PSO-Based Approach 304
5.1 Particle Representation 304
5.2 Fitness Function 304
5.3 Velocity and Position Update 305
6 DE-Based Approach 305
6.1 Vector Representation 305
6.2 Fitness Function 305
6.3 Mutation 305
6.4 Crossover 305
6.5 Selection 306
7 GSA-Based Approach 306
7.1 Agent Representation 306
7.2 Update Velocity, Mass, Position, and Force 306
7.3 Fitness Function 307
8 Experimental Results 307
9 Conclusion 308
References 309
Swarm Intelligent Based Detection in the Uplink of Large-Scale MIMO Wireless Communication Systems 313
1 Introduction 314
2 System Model 316
3 Traditional Detection Techniques 317
3.1 Zero Forcing 317
3.2 Minimum Mean Square Error 319
3.3 Maximum Likelihood Detection and Sphere Decoder 319
4 SSO-Based Large MIMO Detection 320
5 ACO-Based Large MIMO Detection 323
6 Simulation Results and Discussion 324
7 Conclusion 327
References 328
A Nonlinear Strategy Management Approach in Software-Defined Ad hoc Network 331
1 Introduction 332
1.1 Emergence Role in Softwarization 332
1.2 Frameworks and Architectures 333
1.3 Applications of SDANET in Social Networking 334
1.4 Implementation Issues and Prospective Solutions 334
1.5 Motivations 336
1.6 Our Contributions 336
1.7 Structure of the Paper 337
2 Literature Review 337
3 Proposed Model 338
3.1 Outline 338
3.2 Network Model 339
3.3 Parameter Structure 341
3.4 Strategy Mapping for Route Selection 342
3.5 Nonlinear Formulation for Route Selection 344
4 Simulation Environment and Performance Analysis 347
4.1 Simulation Model 349
4.2 Performance Metrics 349
5 Conclusion 353
References 353
Image Encryption in IoT Devices Using DNA and Hyperchaotic Neural Network 357
1 Introduction 357
1.1 Internet of Multimedia Things 358
1.2 Encryption Techniques in Images 359
1.3 Latest Trends in Image Encryption Using DNA and Neural Networks 361
2 Relevant Sources of Literature 366
2.1 Neural Network-Based Chaotic System for Encryption 366
2.2 Heterogenous Chaotic Neural Network and DNA Encoding 368
2.3 Color Image Encryption Based on Fractional-Order Hyperchaotic Systems 369
3 Our Proposed Work 369
4 Analysis of the Test Results 380
5 Application 383
6 Conclusion 383
References 384
Design and Implementation of Efficient Routing Protocol 386
Implementation of Traffic Priority Aware Medium Access Control Protocol for Wireless Body Area Networks 387
1 Introduction 388
1.1 Wireless Body Area Network (WBAN) 388
1.2 Architecture of WBAN 389
1.3 Application of WBAN 389
1.4 Superframe Structure 390
1.5 Objective of MAC Layer 392
2 Literature Review 393
3 Problem Statement 394
3.1 Traffic Priority Aware Medium Access Control Protocol (TAMAC) 395
3.2 Suggested Superframe Structure 396
4 Performance Evaluation 400
4.1 Simulation Implementation 401
4.2 Analysis of Results 402
5 Conclusion 404
References 404
Enhanced Shortest Path Routing Protocol Using Fuzzy C-Means Clustering for Compromised WSN to Control Risk 406
1 Introduction 407
2 Related Work 408
3 Proposed Work 409
3.1 Network Model 409
3.2 Reputation System in WSN 409
3.3 Enhanced Secure Shortest Path Routing with CRs 410
4 Performance Assessment and Result 414
4.1 Simulation Setup 415
4.2 Success Rate of Package Delivery 415
4.3 Average Length of the Routing Paths 416
4.4 Totality in Transmitting the Data 418
4.5 Energy Efficiency of ESPRA 419
4.6 Performance Discussion 419
5 Conclusion 420
References 421
Fuzzy Petri Nets-Based Intelligent Routing Protocol for Ad Hoc Network 423
1 Introduction 423
2 Related Works 424
3 Preliminaries 427
3.1 Fuzzy Logic 427
3.2 Petri Nets 428
4 Proposed Work 428
4.1 Evaluation of FC 429
4.2 Route Selection by Using FPN 431
5 Performance Evaluation 434
6 Conclusion 437
References 437
Erscheint lt. Verlag | 10.8.2019 |
---|---|
Reihe/Serie | Lecture Notes in Networks and Systems | Lecture Notes in Networks and Systems |
Zusatzinfo | XXI, 433 p. 182 illus., 108 illus. in color. |
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Maschinenbau | |
Technik ► Nachrichtentechnik | |
Schlagworte | Ad-Hoc Network • Aggregation Technique • Automation System • Intelligence System • Optimization • routing protocol • Wireless Body Area Network • wireless sensor network |
ISBN-10 | 981-13-9574-8 / 9811395748 |
ISBN-13 | 978-981-13-9574-1 / 9789811395741 |
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