EBOOK - Physical Layer Security for 6G Networks (Trung Q. Duong & Junqing Zhang) Full | Cộng đồng Kỹ thuật cơ điện Việt Nam EBOOKBKMT

Bảo mật lớp vật lý cho mạng 6G (Trung Q. Dương & Junqing Zhang)

6G networks are expected to provide one-microsecond latency communication with a billion devices competing for resources 1000 times faster than current standards. Increases in network speed, heterogeneity, virtualization, better radio requirements and adaptive communications will place new demands on physical layer security. Moreover, IoT, blockchain, and artificial intelligence are enabling technologies that require rapid data rates, raising a significant burden on the network's physical layer, requiring that security must be attained at a fast pace, and that the network must be resilient to accommodate sudden changes to the configurations or the load.

Physical layer (PHY) security solutions are needed that have the capacity to handle the new demands of 6G networks, whilst protecting those networks against risk factors such as interference, data spoofing, replay attacks, side-channel attacks, jamming, traffic analysis, and cyber-vandalism attacks. This comprehensive book addresses the PHY security challenges and proposes efficient and resilient physical layer security solutions for beyond 5G networks leading to 6G. Several topics have emerged that rely on PHY security in solving real-world network challenges such as ultra-dense networks, adaptive communication, distributed technology, and artificial intelligence.

Physical Layer Security for 6G Networks helps readers understand the expectations of 6G's physical layer security in supporting pervasive and integrated communication networks, AI convergence and utility, and develop better sensing solutions, which go beyond cognitive radio, device-to-device or mm-wave communications.

CONTENTS:

Part I: Fundamental theories of physical layer security 1

1 Learned codes for dependent wiretap channels 3

Karl-Ludwig Besser, Pin-Hsun Lin and Eduard A. Jorswieck

1.1 Introduction 3

1.1.1 State of the art 5

1.1.2 Outline of chapter 9

1.2 Preliminaries 9

1.2.1 System model 9

1.2.2 Reliability and confidentiality 10

1.2.3 Transmissions over multiple blocks in slow two-state

fading 11

1.2.4 General distributions of the channels 14

1.3 Autoencoder-based wiretap code design 17

1.3.1 Problem formulation 17

1.3.2 Feed-forward neural networks 18

1.3.3 Implementation by autoencoders 19

1.4 Numerical assessments 22

1.4.1 Dependent fading channels with a single connectivity 25

1.4.2 Dependent fading channels with multiple connections 27

1.5 Conclusions and future work 30

References 31

2 Physical layer security in the terahertz band 37

Weijun Gao and Chong Han

2.1 Fundamental system model for THz secure communications 38

2.1.1 THz channel model 38

2.1.2 Performance metrics for THz secure communications 42

2.1.3 Challenges of THz physical layer security 44

2.2 Fundamental system model for THz covert communications 45

2.2.1 Hypothesis testing for covert communications 45

2.2.2 Covert outage probability 46

2.2.3 Signal-to-noise-ratio wall 47

viii Physical layer security for 6G networks

2.3 Distance-adaptive molecular absorption peak modulation scheme 50

2.3.1 DA-APM design guideline 51

2.4 Molecular absorption-assisted SIC-free receiver artificial noise

scheme 52

2.4.1 Temporal broadening effect 53

2.4.2 SIC-free receiver AN scheme 55

2.4.3 Eavesdroppable region analysis 57

2.4.4 Waveform parameter design guideline 59

2.5 Widely spaced antenna communications for THz physical

layer security 60

2.5.1 Widely spaced array and beamforming 61

2.5.2 Beamforming design guideline 62

2.6 Conclusion and future directions 64

References 64

3 Eavesdropping attacks for terahertz wireless links 67

Jianjun Ma, Yige Qiao and Houjun Sun

3.1 Introduction 67

3.2 Security performance characterization 68

3.2.1 Blockage 68

3.2.2 Secrecy capacity 69

3.2.3 Backscattering parameter 69

3.2.4 Outage probability 70

3.3 Eavesdropping attacks in indoor terahertz links 70

3.3.1 Attacks in LoS link 70

3.3.2 Attacks in non-LoS link 72

3.4 Eavesdropping attacks in outdoor terahertz links 74

3.4.1 Deterministic evaluation 75

3.4.2 Probabilistic evaluation 77

3.5 Conclusion 78

Acknowledgments 79

References 79

4 Intelligent reflecting surface-aided physical layer security

of wireless communications 83

Tong-Xing Zheng, Xin Chen, Ying Ju, Haoyu Wang,

Chaowen Liu and Limeng Dong

4.1 Introduction 83

4.1.1 Intelligent reflecting surface-aided physical layer security 83

4.1.2 Recent research and evolution of IRS-aided PLS 84

4.1.3 Contributions and organization 87

4.2 IRS-assisted MIMO secure communications 88

4.2.1 System model and problem description 88

4.2.2 Joint active and passive beamforming design 89

Contents ix

4.2.3 Numerical results and discussions 91

4.2.4 Summary 92

4.3 Enhancing PLS using IRS-empowered pattern index modulations 92

4.3.1 System model and problem description 92

4.3.2 PLS-enhancing schemes for IRS-empowered PIMs 95

4.3.3 Numerical results and discussions 96

4.3.4 Summary 96

4.4 IRS-enabled secure integrated sensing and communication

systems 98

4.4.1 System model and problem description 98

4.4.2 Joint active and passive beamforming design 99

4.4.3 Numerical results and discussions 101

4.4.4 Summary 102

4.5 IRS-aided secure communications: a deep reinforcement learning

perspective 102

4.5.1 System model and problem formulation 103

4.5.2 DRL-based scheme 105

4.5.3 Summary 109

4.6 Conclusions and future works 109

References 110

Part II: Authentication using channel features and

hardware impairments 115

5 Intelligent physical layer authentication 117

Yun Ma, He Fang, Xianbin Wang and Li Xu

5.1 Introduction 117

5.2 System model 121

5.3 BPNN-based intelligent physical layer authentication:

a nonparametric method 123

5.3.1 BPNN-based multiple physical layer attribute fusion 124

5.3.2 Adaptive authentication process based on BPNN 128

5.3.3 Simulation results 128

5.4 FL-based intelligent physical layer authentication: a parametric

method 134

5.4.1 FL-based multiple attribute fusion model 134

5.4.2 Multi-dimensional adaptive authentication process 138

5.4.3 Simulation results 141

5.5 Conclusions and future researches 144

References 145

6 Deep learning-enhanced radio frequency fingerprint identification 149

Guanxiong Shen, Junqing Zhang and Alan Marshall

6.1 Introduction 149

6.2 Related work 151

x Physical layer security for 6G networks

6.3 System overview and problem statement 152

6.3.1 System overview 152

6.3.2 Problem statement 153

6.4 System design 153

6.4.1 Signal processing 153

6.4.2 Training data collection and data augmentation 154

6.4.3 Signal representation 154

6.4.4 Neural network 155

6.5 Case study: LoRa-RFFI system 155

6.5.1 LoRa physical layer primer 155

6.5.2 Signal processing 156

6.5.3 Data augmentation 157

6.5.4 Signal representation 159

6.5.5 Neural network 160

6.6 Experimental evaluation 161

6.6.1 Experimental settings 161

6.6.2 Effect of locations 161

6.6.3 Performance in different SNR scenarios 162

6.6.4 Performance of the frequency offset compensation

algorithm 163

6.6.5 Effect of frequency offset compensation on

RFFI performance 164

6.7 Conclusion 165

References 165

7 Radio frequency fingerprint-based wireless device identification 169

Ming Liu, Hui Luo, Xin Wang, Linning Peng and Hua Fu

7.1 Security risks in wireless networks 169

7.2 Radio frequency fingerprint 172

7.2.1 Properties of RF fingerprint 172

7.2.2 Source of RF fingerprint 173

7.2.3 RF fingerprint-based device identification 177

7.2.4 State-of-the-art 179

7.3 Case study: RFF extraction of Bluetooth devices 183

7.4 Deep learning-based device identification 186

7.4.1 CNN-based known device verification 186

7.4.2 Anomaly detection-based unknown device detection 188

7.4.3 Performance evaluation and analysis 191

7.5 Open questions and potential research directions 194

7.5.1 High capacity fingerprint for massive devices 194

7.5.2 Channel-independent fingerprint extraction 195

7.5.3 Security of RF fingerprint 196

Acknowledgments 197

References 197

Contents xi

Part III: Key generation from wireless channels 205

8 Secret key generation from wireless channels 207

Magnus Sandell

8.1 Introduction 207

8.1.1 Secret key rate 208

8.1.2 Key generation 210

8.2 Channel sounding 211

8.2.1 Channel probing 211

8.2.2 Static environments 211

8.2.3 Precoding 212

8.2.4 Reciprocity 214

8.2.5 Frequency-division duplex 214

8.3 Feature extraction 215

8.3.1 RSSI 215

8.3.2 Frequency response 216

8.3.3 Spatial domain 216

8.3.4 Decorrelation 217

8.3.5 Other processing 218

8.4 Channel quantisation 218

8.4.1 Scalar quantisation 218

8.4.2 Vector quantisation 219

8.4.3 Statistical properties 220

8.5 Information reconciliation 221

8.6 Privacy amplification 224

8.7 Multidevice networks 227

8.8 Summary 230

References 230

9 Impact of reconfigurable intelligent surfaces on physical layer key

generation in NextG wireless networks 237

Guyue Li, Lei Hu, Long Jiao, Kai Zeng, Chen Sun and Aiqun Hu

9.1 Introduction 237

9.2 New changes in fundamentals when PKG meets RIS 239

9.2.1 Fundamentals of PKG 239

9.2.2 RIS-involved channel model 239

9.2.3 Implications of RIS-involved channel 240

9.3 RIS-assisted PKG: potential improvements 240

9.3.1 Case I: static environments 241

9.3.2 Case II: wave-blockage environments 251

9.4 RIS-based attacks and countermeasures 256

9.4.1 RIS jamming (RISJ) attack 256

9.4.2 RIS leakage (RISL) attack 262

9.5 Conclusion and future directions 265

Acknowledgments 266

References 266

xii Physical layer security for 6G networks

10 Physical layer key generation for LoRa-enabled networks 271

Huanqi Yang, Zehua Sun and Weitao Xu

10.1 Introduction 271

10.2 Background 272

10.2.1 Primer on LoRa 272

10.2.2 Primer on wireless key generation 275

10.3 Key-generation schemes for LoRa-enabled networks 280

10.3.1 LoRa key-generation scheme in various environments 280

10.3.2 LoRa key generation scheme for COTS LoRaWAN 281

10.3.3 LoRa key-generation scheme using different channel

parameters 284

10.3.4 LoRa key-generation scheme for long-range and highly

mobile scenarios 285

10.4 Conclusion 287

References 287

11 Robust secret key generation from stochastic fading in the presence

of passive and active attackers 291

Arsenia Chorti

11.1 Introduction and chapter organization 291

11.2 General directions for incorporating PLS in 6G 292

11.2.1 Roadmap for incorporating PLS in 6G 293

11.2.2 Robust SKG 295

11.3 SKG reconciliation rates in short blocklengths 298

11.4 Robust SKG against eavesdropping by a nearby attacker 301

11.4.1 Proposed statistical independence metric 302

11.4.2 Reciprocity and mismatch probability 303

11.4.3 Proposed power domain pre-processing 303

11.4.4 Pre-processing using PCA 304

11.5 Man-in-the-middle attacks on SKG and countermeasures 307

11.6 Analysis of denial of service attacks on SKG 309

11.6.1 Optimal power allocation strategies 311

11.6.2 Stackelberg equilibrium with fixed sensing thresholdpth 311

11.7 Novel hybrid SKG-cryptosystems 312

11.7.1 Authenticated encryption using SKG 313

11.7.2 SKG for zero-round-trip time protocols (0-RTT) 315

11.8 Concluding remarks and future perspectives 316

References 318

12 Physical-layer key generation for multi-user massive MIMO

wireless communications 323

Chen Sun, Guyue Li, Hongyi Luo and Aiqun Hu

12.1 Introduction 323

12.2 System model for massive MIMO key generation 325

12.2.1 Traditional secret key generation model 326

12.2.2 Massive MIMO channel model 327

Contents xiii

12.3 General CDR-based key-generation scheme 330

12.3.1 Key-generation scheme based on CDR 330

12.3.2 Secret key rate 332

12.4 Optimization design of CDR-based key generation 333

12.4.1 Design of precoding and receiving directions 334

12.4.2 Design of transmitted power allocation 336

12.5 Security analysis 340

12.6 Numerical result 341

12.7 Conclusions 347

Acknowledgments 348

References 348

Part IV: Applications of physical layer security 351

13 Physical layer security for UAV wireless networks 353

Chenxi Liu, Rui Ma, Jemin Lee and Tony Q.S. Quek

13.1 Introduction 353

13.2 System model 356

13.2.1 Ground-to-UAV channel model 356

13.2.2 Transmission of AN signals 359

13.2.3 Active eavesdropping 359

13.3 Hybrid outage probability analysis 361

13.3.1 Statistics of SINRs 361

13.3.2 Hybrid outage probability 362

13.3.3 Asymptotic analysis of hybrid outage probability 365

13.3.4 Passive eavesdropping 366

13.4 Simulations and numerical analysis 367

13.4.1 Optimal configuration of legitimate system 367

13.4.2 Optimal configuration of eavesdropper 371

13.5 Conclusions and future works 373

References 374

14 Secure communication in mobile edge computing networks with RF

energy harvesting 379

Dac-Binh Ha, Van-Long Nguyen, Van-Truong Truong and Anand Nayyar

14.1 Introduction 380

14.2 Literature review 382

14.3 System channel and model 383

14.3.1 Relay and user selection solution 385

14.3.2 NOMA-based DF relay offloading with

RF EH description 386

14.3.3 Derivation for the joint CDF of SINRs and SNRs 387

14.4 Secrecy performance analysis 388

14.4.1 Preliminaries 389

14.4.2 Existence probability of secrecy capacity analysis 389

xiv Physical layer security for 6G networks

14.4.3 Secrecy outage probability analysis 391

14.4.4 Secrecy performance optimization 392

14.5 Numerical results and discussion 394

14.6 Conclusion and future scope 403

Appendix A: Proof of Lemma 1 403

Appendix B: Proof of Lemma 2 404

Appendix C: Proof of Theorem 3 405

Appendix D: Proof of Theorem 4 406

Appendix E: Proof of Theorem 5 406

Appendix F: Proof of Theorem 6 408

References 408

15 Secure and private localization in 6G networks 413

Stefano Tomasin, Shihao Yan and Robert Malaney

15.1 Location verification 414

15.1.1 Physical-layer-based location verification 414

15.1.2 Machine-learning-based location verification 415

15.1.3 Simultaneous location reporting and verification 418

15.2 Location privacy 419

15.2.1 Location privacy in mobile networks 420

15.2.2 5G and beyond networks 422

15.2.3 Localization techniques 424

15.2.4 Singe-UE privacy using AoA-based localization 426

15.2.5 Singe-UE privacy using RSS-based localization 427

15.2.6 Single-UE privacy using TDoA-based localization 427

15.2.7 Cooperative location-preserving privacy technique 429

15.3 Quantum-enhanced location privacy and authentication 432

References 437

16 Radio frequency informed physical layer security—an augmented

padlock to wireless transmission secrecy 443

Jayakrishnan M. Purushothama, Jiayu Hou, Yuan Ding and Yue Xiao

16.1 What is physical layer wireless security, and why it is important 443

16.2 Broad classification of physical layer wireless security 444

16.3 Directional modulation (DM) 445

16.3.1 A general mathematical description of DM with

reference to conventional transmission 446

16.3.2 Software-centered approaches for DM 449

16.3.3 Hardware-centered approaches for DM 455

16.3.4 Emerging DM techniques for low-cost and

high-efficiency applications 463

16.4 Inter-system benchmarking and other considerations 466

16.4.1 Metrics for DM evaluation 466

16.4.2 DM power efficiency 467

16.5 Conclusion, future perspectives, and other discussions 468

Acknowledgments 469

References 469

Contents xv

17 Physical layer security for non-orthogonal multiple access

toward 6G 477

Na Li and Yuanwei Liu

17.1 Brief review of PLS for NOMA toward 6G 477

17.1.1 NOMA with new modulation: OTFS-NOMA 478

17.1.2 NOMA with new spectrums:

mmWave/THz/VLC-NOMA 478

17.1.3 NOMA with new random access: GF-NOMA 480

17.1.4 NOMA with new schemes: ISAC/BC-NOMA 480

17.1.5 NOMA with RIS: RIS-NOMA 482

17.1.6 Conclusion in open problems and research directions 483

17.2 Motivation 484

17.2.1 RIS-NOMA under external eavesdropping 485

17.2.2 RIS-NOMA under internal eavesdropping 485

17.3 Secure NOMA communication against the external eavesdropper

assisted by STAR-RIS 486

17.3.1 System model and problem formulation 486

17.3.2 Problem formulation and proposed solution 487

17.3.3 Simulation results 491

17.3.4 Conclusion 496

17.4 Heterogeneous internal secrecy for NOMA assisted by RIS 497

17.4.1 System model 497

17.4.2 Problem formulation and derivations 498

17.4.3 Numerical results 502

17.4.4 Conclusion 504

References 504

18 Detecting unpredictable adversaries in the industrial network with

blockchain 511

Vishal Sharma, Aman Kataria, John McAllister, Amie Weedon

and Robert Bennett

18.1 Introduction 511

18.2 Digital warfare and cyber-vandalism 513

18.3 Unpredictable adversaries 514

18.3.1 Zero-click adversaries 514

18.3.2 Challenges in detecting unpredictable adversaries 514

18.4 Attacks by unpredictable adversaries 516

18.5 Validating ICPS workflow using blockchain 517

18.5.1 Entities 517

18.5.2 Model for event validation 519

18.6 Future research trends 522

18.7 Conclusion 523

References 523

xvi Physical layer security for 6G networks

19 Using support vector machines for detecting active spoofing attacks 527

Tiep M. Hoang and Trung Q. Duong

19.1 Introduction 527

19.2 A brief introduction to TC-SVM and SC-SVM 529

19.2.1 The development of typical models 529

19.2.2 Kernel methods 530

19.2.3 Classification based on twin-class SVM 531

19.2.4 Classification based on SC-SVM 534

19.3 Collecting wireless signals and creating/defining features 535

19.3.1 Collecting wireless data 535

19.3.2 Creating features/attributes 536

19.4 Artificial training data 538

19.4.1 ATD for twin-class SVM 538

19.4.2 ATD for single-class SVM 540

19.4.3 ATD normalization/whitening 540

19.5 Numerical results 541

19.5.1 ExaminingT,T, andT0 541

19.5.2 Examining four different kernel functions 542

19.5.3 Receiver operating characteristic curves and

sensitivity-specificity trade-off 543

19.5.4 Examining the impact ofρEandγ 546

19.5.5 Over-fitting problems: the impact ofγ 546

19.6 Conclusions 548

References

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Bảo mật lớp vật lý cho mạng 6G (Trung Q. Dương & Junqing Zhang)

CONTENTS: