About the Editors xxiii

List of Contributors xxvii

Preface xxxv

1 Introduction to TinyML 1
Francisca Onyiyechi Nwokoma, Chidi Ukamaka Betrand, Juliet Nnenna Odii, Euphemia Chioma Nwokorie, and Ikechukwu Ignatius Ayogu

1.1 Introduction 1

1.2 Evolution of TinyML 6

1.3 Key Milestones and Current Trends 8

1.4 TinyML System Development 11

1.5 Challenges and Bottlenecks 17

1.6 Cost-Benefit Analysis 20

1.7 Key Findings 26

1.8 Limitations of TinyML 27

1.9 Conclusion 29

References 30

2 Learning Panorama Under TinyML 35
Ikechukwu Ignatius Ayogu, Euphemia Chioma Nwokorie, Juliet Nnenna Odii, Francisca Onyiyechi Nwokoma, and Chidi Ukamaka Betrand

2.1 Introduction 35

2.2 Challenges and Opportunities for Improved TinyML Model Design 37

2.3 Frontiers in Model Optimization for TinyML 47

2.4 Learning Frameworks and Tools for TinyML Development 59

2.5 Frontiers for Algorithmic Innovations for TinyML 63

2.6 TinyML Development Process 68

2.7 Key Findings 69

2.8 Conclusion 70

References 71

3 TinyML for Anomaly Detection 85
Richard Govada Joshua, Peter Anuoluwapo Gbadega, Agbotiname Lucky Imoize, and Samuel Oluwatobi Tofade

3.1 Introduction 85

3.2 Context and Literature Review 93

3.3 Lessons Learned 149

3.4 Future Scope 152

3.5 Conclusion 156

References 157

4 TinyML Power Consumption and Memory in IoT MCUs 163
Peter Anuoluwapo Gbadega, Agbotiname Lucky Imoize, Richard Govada Joshua, and Samuel Oluwatobi Tofade

4.1 Introduction 163

4.2 Context and Literature Review 171

4.3 Methodology 174

4.4 Results and Discussion: Bibliometric Analysis 184

4.5 Conclusion and Future Directions 198

References 199

5 Efficient Data Cleaning and Anomaly Detection in IoT Devices Using TinyCleanEDF 205
Ilker Kara

5.1 Introduction 205

5.2 IoT and TinyCleanEDF 206

5.3 The Importance of Data Cleaning in IoT Systems 207

5.4 Anomaly Detection and Its Importance in IoT Systems 208

5.5 Data Preprocessing and Cleaning Workflow 209

5.6 Implementation Details 213

5.7 Case Studies and Applications 216

5.8 Future Directions 219

5.9 Conclusion and Future Scope 221

References 222

6 TinyML Devices and Tools 225
Abeeb Akorede Bello, Agbotiname Lucky Imoize, and Abiodun Temitope Odewale

6.1 Introduction 225

6.2 Related Work 227

6.3 TinyML Devices 234

6.4 TinyML Tools 237

6.5 Deployment Procedure of TinyML 241

6.6 Lesson Learned and Prospects 250

6.7 Conclusion 253

References 254

7 Privacy-Preserving Techniques in TinyML for IoT 259
Oleksandr Kuznetsov, Emanuele Frontoni, Kateryna Kuznetsova, Marco Arnesano, and Pavlo Usik

7.1 Introduction 259

7.2 Related Works 261

7.3 Homomorphic Encryption in TinyML 262

7.4 Differential Privacy for TinyML 271

7.5 Secure Multi-Party Computation in TinyML 277

7.6 Case Studies and Applications of Privacy-Preserving TinyML 281

7.7 Discussion and Future Directions 293

7.8 Conclusion 296

Acknowledgment 296

References 296

8 Enhancing Cybersecurity in TinyML with Lightweight Cryptographic Algorithms 303
Oleksandr Kuznetsov, Roman Minailenko, Aigul Shaikhanova, Yelyzaveta Kuznetsova, and Agbotiname Lucky Imoize

8.1 Introduction 303

8.2 Literature Review 305

8.3 Lightweight Cryptographic Algorithms for TinyML 306

8.4 Comparative Analysis of Lightweight Block Ciphers 315

8.5 Comparative Analysis of Lightweight Hash Functions 318

8.6 Comparative Analysis of Lightweight Stream Ciphers 322

8.7 Implementation Strategies for Lightweight Cryptography in TinyML 325

8.8 Conclusion 327

Acknowledgment 328

References 329

9 Tiny Machine Learning for Enhanced Edge Intelligence 335
Emmanuel Alozie, Agbotiname Lucky Imoize, Hawau I. Olagunju, Nasir Faruk, Salisu Garba, and Ayobami P. Olatunji

9.1 Introduction 335

9.2 Overview of Tiny Machine Learning (TinyML) 337

9.3 TinyML as a Service (TMLaaS) Architecture 349

9.4 Results and Discussion 354

9.5 Open Challenges and Further Research Directions 357

9.6 Conclusion 358

References 359

10 Advanced Security Schemes for TinyML Devices 367
Wasswa Shafik and Mumin Adam

10.1 Introduction 367

10.2 Fundamentals of TinyML 369

10.3 Privacy Concerns in TinyML 374

10.4 Security and Privacy Solutions 376

10.5 The Implementation of Novel Security Schemes for TinyML Applications 384

10.6 Privacy-Enhancing Techniques for TinyML 388

10.7 Future Directions of Security and Privacy in TinyML Devices 391

10.8 Lessons Learned 393

10.9 Limitations of this Study 394

10.10 Conclusion 395

References 396

11 Robust Ground Truth Data Mining for Enhanced Privacy and Accuracy in Noisy TinyML Environments 403
Yuichi Sei and Agbotiname Lucky Imoize

11.1 Introduction 403

11.2 Related Research Work 406

11.3 Models 408

11.4 Gdp 412

11.5 Evaluation 416

11.6 Discussion 420

11.7 Conclusions 423

References 424

12 Security and Privacy of TinyML Devices 431
Eftychia Mistillioglou, Evangelia Konstantopoulou, Nicolas Sklavos, and Andronikos Kyriakou

12.1 Introduction 431

12.2 Related Work 433

12.3 Secure and Privacy-Aware Training of TinyML Models 437

12.4 Implementation of Novel Security Schemes for TinyML Applications 455

12.5 Lessons, Challenges, and Future Directions 463

12.6 Conclusions and Outlook 464

References 465

13 Semantic Management of TinyML for Industrial Application 469
Kinzah Noor, Hasnain Ahmad, and Agbotiname Lucky Imoize

13.1 Introduction 469

13.2 Introduction to TinyML 472

13.3 Recent Advances in TinyML 477

13.4 Methodology 488

13.5 Results and Discussion 495

13.6 Conclusions and Future Scope 498

References 498

14 Fight Poison with Poison: Tiny Machine Learning Resilience Against Poisoning Attacks 503
Tomoki Chiba, Yasuyuki Tahara, Akihiko Ohsuga, Agbotiname Lucky Imoize, and Yuichi Sei

14.1 Introduction 503

14.2 Problem Definition 505

14.3 Related Work 507

14.4 Proposed Method 512

14.5 Evaluation Experiment 523

14.6 Discussion 541

14.7 Conclusion 543

References 544

15 TinyML for Real-Time Medical Image Classification and Diagnosis 549
Jelil O. Agbo-Ajala, Lateef A. Akinyemi, Olufisayo S. Ekundayo, and Ernest Mnkandla

15.1 Introduction 549

15.2 Literature Review 551

15.3 Methodology 566

15.4 Results and Discussion 567

15.5 Conclusion 578

References 578

16 Biometric Authentication in TinyML: Opportunities and Challenges 587
Oleksandr Kuznetsov, Emanuele Frontoni, Marco Arnesano, Oleksii Smirnov, and Boris Khruskov

16.1 Introduction 587

16.2 Related Work 589

16.3 Overview of Biometric Authentication Techniques 591

16.4 Comparative Analysis of Biometric Authentication Methods 609

16.5 Adapting Biometric Techniques for TinyML Systems 615

16.6 Discussion and Future Directions 625

16.7 Conclusion 628

Acknowledgment 628

References 629

17 Secure Deployment of TinyML Applications: Strategies and Practices 635
Oleksandr Kuznetsov, Sergii Kavun, and Gulvira Bekeshova

17.1 Introduction 635

17.2 Related Work 636

17.3 Security Architectures for TinyML Deployments 638

17.4 Secure Bootstrapping and Key Management 643

17.5 Secure Communication Protocols for TinyML 646

17.6 Data Privacy in TinyML Applications 650

17.7 Future Directions and Emerging Technologies 652

17.8 Conclusion 655

Acknowledgment 657

References 657

18 TinyML for Environmental Applications 665
Duy Nam Khanh Vu and Anh Khoa Dang

18.1 Introduction 665

18.2 Related Work 667

18.3 Methodology 669

18.4 Case Study: New Insights on Air Writing from Plawiak and Alblehai 689

18.5 Results and Discussion 692

18.6 Conclusion and Future Scope 697

References 697

19 Benchmarking TinyML Encrypted Federated Learning with Secret Sharing in Medical Computer Vision 701
Ruduan B. F. Plug, Putu H. P. Jati, Samson Y. Amare, and Mirjam van Reisen

19.1 Introduction 701

19.2 Related Work 702

19.3 Methodology 703

19.4 Results 711

19.5 Conclusion 715

References 716

Index 721