Physical-Layer Security for 6G
Description
Meet the wireless security challenges of the future with this key volume
The 6th generation of wireless communication technology-known as 6G-promises to bring both revolutionary advances and unique challenges. Secure communications will be harder than ever to achieve under the new integrated ground, air, and space networking paradigm, with increased connectivity creating the potential for increased vulnerability. Physical-layer security, which draws upon the physical properties of the channel or network to secure information, has emerged as a promising solution to these challenges.
Physical-Layer Security for 6G provides a working introduction to these technologies and their burgeoning wireless applications. With particular attention to heterogeneous and distributed network scenarios, this book offers both the information-theory fundamentals and the most recent developments in physical-layer security. It constitutes an essential resource for meeting the unique security challenges of 6G.
Physical-Layer Security for 6G readers will also find:
- Analysis of physical-layer security in the quality of security framework (QoSec)
- Detailed discussion of physical-layer security applications in visible light communication (VLC), intelligence reflecting surface (IRS), and more
- Practical use cases and demonstrations
Physical-Layer Security for 6G is ideal for wireless research engineers as well as advanced graduate students in wireless technology.
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Persons
Parthajit Mohapatra, PhD, is Associate Professor in the Department of Electrical Engineering, Indian Institute of Technology, India. His research focuses on physical-layer secrecy, short packet communication, union of networking & physical-layer techniques, and related areas.
Nikolaos Pappas, PhD, is Associate Professor in the Department of Computer and Information Science, Linköping University, Sweden. His research concerns semantic wireless communications, network-level cooperative wireless networks, stochastic modeling, and related subjects.
Arsenia Chorti, PhD, is Professor and Head of the Information, Communications and Imaging (ICI) Group of the ETIS Lab UMR8051, CY Cergy Paris Universite, France, and a Visiting Research Scholar at Princeton University, USA, and the University of Essex, UK. Her research focuses on physical-layer security, especially context-aware security, intrusion detection in IoT networks, and related subjects.
Stefano Tomasin, PhD, is Professor at the University of Padova, Italy. His research concerns physical-layer security and signal processing for wireless communications, and he serves as Deputy EiC of the IEEE Transactions on Information Forensics and Security.
Content
About the Editors xiii
List of Contributors xv
Preface xix
Part I Preliminaries 1
1 Foundations of Physical-Layer Security for 6G 3
Matthieu Bloch
1.1 Coding Mechanisms 4
1.1.1 Channel Coding 5
1.1.2 Soft Covering 6
1.1.3 Source Coding with Side Information 7
1.1.4 Privacy Amplification 8
1.2 Coding for Physical-Layer Security 8
1.2.1 Secure Communication 9
1.2.2 Secret-Key Generation 11
1.3 Engineering and Learning Channels 12
References 13
2 Coding Theory Advances in Physical-Layer Secrecy 19
Laura Luzzi
2.1 Introduction 19
2.2 Wiretap Coding Schemes Based on Coset Coding 20
2.2.1 LDPC Codes for Binary Erasure Wiretap Channels 21
2.2.2 Polar Codes for Binary Input Symmetric Channels 26
2.2.3 Lattice Codes for Gaussian and Fading Wiretap Channels 29
2.3 Wiretap Coding Schemes Based on Invertible Extractors 31
2.3.1 Secrecy Capacity-Achieving Codes for the Gaussian Channel 35
2.4 Finite-Length Results 35
References 38
Part II Physical-Layer Security in Emerging Scenarios 43
3 Beamforming Design for Secure IRS-Assisted Multiuser MISO Systems 45
Dongfang Xu, Derrick Wing Kwan Ng, and Robert Schober
3.1 Introduction 45
3.2 System Model 47
3.3 Resource Allocation Optimization Problem 49
3.3.1 Performance Metrics of Secure Communication 49
3.3.2 Problem Formulation 50
3.4 Solution of the Optimization Problem 50
3.4.1 Problem Reformulation 50
3.4.2 Successive Convex Approximation 52
3.4.3 Complex Circle Optimization 53
3.4.3.1 Tangent Space 54
3.4.3.2 Riemannian Gradient 54
3.5 Experimental Results 58
3.5.1 Average SSR Versus BS Power Budget 59
3.5.2 Average SSR Versus Number of Legitimate Users 60
3.6 Conclusion 61
3.7 Future Extension 61
References 63
4 Physical-Layer Security for Optical Wireless Communications 67
Shenjie Huang, Mohammad Dehghani Soltani, and Majid Safari
4.1 Introduction 67
4.2 PLS for SISO VLC 68
4.2.1 PLS Performance Metrics 68
4.2.2 SISO VLC Secrecy Analysis 69
4.3 PLS for MISO VLC 74
4.3.1 MISO VLC Secrecy Analysis 75
4.3.2 Secrecy Improvement in MISO VLC 77
4.4 PLS for Multiuser VLC 80
4.4.1 Precoding Designs 80
4.4.2 PLS for NOMA-Based VLC 84
4.5 PLS for VLC with Emerging Technologies 86
4.6 Open Challenges and Future Works 90
References 92
5 The Impact of Secrecy on Stable Throughput and Delay 99
Parthajit Mohapatra and Nikolaos Pappas
5.1 Introduction 99
5.1.1 Related Works 100
5.2 System Model 101
5.3 Stability Region for the General Case 103
5.3.1 First Dominant System 103
5.3.2 Second Dominant System 104
5.4 Stability Region Analysis: Receivers with Different Decoding Abilities 105
5.4.1 Receivers with Limited Decoding Abilities 106
5.4.1.1 When Only the Second Queue Is Non-empty 106
5.4.1.2 When Only the First Queue Is Non-empty 106
5.4.1.3 When Both the Queues Are Non-empty 107
5.4.2 Receiver 1 with Limited Decoding Ability and Receiver 2 Uses SD 109
5.5 Impact of Secrecy on Delay Performance 109
5.5.1 Delay Analysis for User with Confidential Data 109
5.6 Results and Discussion 110
5.6.1 Stability Region with Secrecy Constraint 111
5.6.2 Impact of Imperfect Self-interference Cancelation on the Stability Region 112
5.6.3 Impact of Secrecy on Delay 112
5.7 Conclusion 114
References 114
6 Physical-Layer Secrecy for Ultrareliable Low-Latency Communication 117
Parthajit Mohapatra and Nikolaos Pappas
6.1 Introduction 117
6.2 Background 118
6.2.1 Finite Block-Length Information Theory 118
6.2.1.1 Results for the AWGN Channel 119
6.2.1.2 Results for the AWGN Wiretap Channel 119
6.2.1.3 Stability Criteria of a Queue 119
6.2.1.4 Age of Information 119
6.2.2 Related Works 120
6.3 System Model 121
6.4 Impact of Secrecy on Stable Throughput 122
6.5 Impact of Secrecy on Latency 125
6.5.1 Delay Analysis 125
6.5.2 AAoI Analysis 126
6.6 Results and Discussion 126
6.7 Conclusion 130
References 130
Part III Integration of Physical-layer Security with 6g Communication 133
7 Security Challenges and Solutions for Rate-Splitting Multiple Access 135
Abdelhamid Salem and Christos Masouros
7.1 Introduction 135
7.2 Security Issues in RSMA 137
7.3 How Much of the Split Signal Should Be Revealed? 138
7.3.1 Ergodic Rates 140
7.3.2 Power Allocation Strategy for Secure RSMA Transmission 142
7.4 Secure Beamforming Design for RSMA Transmission 146
7.4.1 Optimization Framework 147
7.4.1.1 Perfect CSIT 147
7.4.1.2 Imperfect CSIT 148
7.5 Conclusion 150
References 151
8 End-to-End Autoencoder Communications with Optimized Interference Suppression 153
Kemal Davaslioglu, Tugba Erpek, and Yalin Sagduyu
8.1 Introduction 153
8.2 Related Work 156
8.3 System Model 157
8.4 Performance Evaluation of AEC Considering the Effects of Channel, Quantization, and Embedded Implementation 159
8.4.1 Comparison of Signal Constellations 160
8.4.2 Effects of EVM 163
8.4.3 Effects of Quantization 163
8.4.4 Practical Considerations for Embedded Devices 164
8.5 Data Augmentation to Train the AE Model Using GANs 166
8.5.1 BER Performance with GAN-Based Data Augmentation 168
8.6 Methods to Suppress the Effects of Interference 169
8.7 AE Communications with Interference Suppression for MIMO Systems 177
8.8 Conclusion 179
References 179
9 AI/ML-Aided Processing for Physical-Layer Security 185
Muralikrishnan Srinivasan, Sotiris Skaperas, Mahdi Shakiba Herfeh, and Arsenia Chorti
9.1 Introduction 185
9.1.1 Facilitating the Incorporation of PLS in 6G 186
9.2 Proposed Metrics for RF Fingerprinting and SKG 187
9.2.1 Total Variation Distance for Radio Frequency Fingerprinting 187
9.2.2 Cross Correlation for SKG 188
9.2.3 Statistical Independence Metric 189
9.2.4 Reciprocity and Mismatch Probability 190
9.3 Power Domain Preprocessing 190
9.3.1 Preprocessing Using PCA 192
9.3.2 Preprocessing Using AEs 195
9.4 Conclusions 198
References 198
10 Joint Secure Communication and Sensing in 6G Networks 203
Miroslav Mitev, Amitha Mayya, and Arsenia Chorti
10.1 Introduction 203
10.2 Related Work and Motivation 205
10.3 System Model 206
10.4 Secret Key Generation Protocol 207
10.4.1 Advantage Distillation 207
10.4.2 Information Reconciliation 208
10.4.3 Privacy Amplification 209
10.5 Measurement Setup 209
10.5.1 Scenarios 210
10.5.2 Implementation of the SKG Protocol 211
10.6 Results and Discussion 212
Acknowledgments 218
References 218
Part IV Applications 221
11 Physical-Layer Authentication for 6G Systems 223
Stefano Tomasin, He Fang, and Xianbin Wang
11.1 Authentication by Physical Parameters 223
11.1.1 PLA and 6G Systems 225
11.2 Challenge-Response PLA for 6G 226
11.3 Intelligent PLA Based on Machine Learning 229
11.3.1 Machine-Learning-Based PLA Approach 231
11.3.2 Performance Analysis 232
References 235
12 Securing the Future e-Health: Context-Aware Physical-Layer Security 239
Mehdi Letafati, Eduard Jorswieck, and Babak Khalaj
12.1 Introduction 239
12.1.1 PHYSEC in 6G 239
12.1.2 Introduction to PHYSEC Solutions 241
12.1.2.1 General Model and Problem Formulations 241
12.1.2.2 Key-less Versus Key-Based Techniques 243
12.1.2.3 Active and Passive Attacks 244
12.2 PHYSEC Key Generation 245
12.2.1 Learning-Aided PHYSEC for e-Health 246
12.2.1.1 Neural Network Implementation 248
12.2.1.2 Information-Theoretic Secrecy Analysis 250
12.2.2 Covert or Stealthy SKG 251
12.2.3 SKG in Multiuser Massive MIMO 252
12.2.4 Robust MiM Attack-Resistant SKG for Multi-carrier MIMO Systems 255
12.3 Key-less PHYSEC for Medical Image Transmission 258
12.3.1 Content- and Delay-Aware Design 259
12.3.1.1 Security Level Adjustment 261
12.3.1.2 Evaluations 262
12.4 Proof-of-Concept Study 263
12.5 Conclusions and Future Directions 266
References 267
13 The Role of Non-terrestrial Networks: Features and Physical-Layer Security Concerns 275
Marco Giordani, Francesco Ardizzon, Laura Crosara, Nicola Laurenti, and Michele Zorzi
13.1 Non-terrestrial Networks for 6G 275
13.1.1 Use Cases 277
13.1.1.1 Continuous and Ubiquitous Network Coverage 277
13.1.1.2 Support for the Internet of Things 277
13.1.1.3 Integration Between Communication and Computation 278
13.1.1.4 Energy-Efficient Service 278
13.1.2 Enabling Technologies 278
13.1.2.1 Novel Network Solutions 278
13.1.2.2 Novel Antenna Solutions 279
13.1.2.3 Novel Spectrum Solutions 279
13.1.3 Open Research Questions 279
13.1.3.1 Physical-Layer Procedures 279
13.1.3.2 Synchronization 280
13.1.3.3 Channel Estimation and Random Access 280
13.1.3.4 Mobility Management 280
13.1.3.5 Resource Saturation 281
13.1.3.6 Higher-Layer Protocol (Re)design 281
13.1.3.7 The Role of the Uplink 282
13.1.3.8 Security and Privacy 282
13.2 Physical-Layer Security in Non-terrestrial Networks 282
13.2.1 Physical-Layer Secrecy in NTNs 283
13.2.1.1 Two-Way Protocols 284
13.2.1.2 Geographical Constraints 284
13.2.1.3 Use of Relays and Friendly Jamming Helpers 285
13.2.2 Physical-Layer Authentication for NTNs 285
13.2.2.1 Device-Based PLA 287
13.2.2.2 Channel-Based PLA 288
13.2.2.3 Challenges and Future Works for PLA 289
13.2.3 Position Integrity for NTNs 290
13.2.3.1 System Model 291
13.2.3.2 Attack Model 293
13.2.3.3 Authentication Procedure 294
13.2.3.4 Performance Metrics 295
13.3 Conclusions 298
References 299
14 Quantum Hardware-Aware Security for 6G Networks 305
Matthias Frey, Igor Bjelakovic, Janis Nötzel, Juliane Krämer, and Slawomir Stanczak
14.1 Introduction 305
14.2 Preliminaries 308
14.2.1 Quantum States and Observables 308
14.2.2 Quantum Channels 309
14.2.3 Bosonic Systems 311
14.2.4 Information Measures 312
14.3 Secret Communication 312
14.3.1 Semantic Security and Its Operational Significance 313
14.3.2 Other Security Measures Used in the Analysis of Secret Communication 315
14.3.3 Survey of Results 316
14.3.3.1 Finite-Dimensional Case 317
14.3.3.2 Infinite-Dimensional Case 318
14.4 Covert Communication 320
14.4.1 System Model 321
14.4.2 Survey of Results 323
14.5 Conclusion 325
Acknowledgments 326
References 326
15 Leveraging the Physical Layer to Achieve Practically Feasible Confidentiality and Authentication 331
Marco Baldi and Linda Senigagliesi
15.1 Introduction 331
15.2 System Model 332
15.3 Confidentiality at the Physical Layer in Practical Settings 335
15.3.1 Joining Physical-Layer Security with Cryptography 336
15.3.2 Dealing with Variable Channel Quality Through On-Off Transmissions 338
15.4 Authentication at the Physical Layer in Practical Settings 342
15.4.1 PLA Metrics 344
15.5 Numerical Experiments 345
15.5.1 Physical-Layer Confidentiality Examples 345
15.5.2 Physical-Layer Authentication Examples 347
15.6 Conclusion 351
References 351
Index 355
1
Foundations of Physical-Layer Security for 6G*
Matthieu Bloch
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Wireless connectivity has become a cornerstone of our modern societies, driving innovation and supporting an ever-growing range of services. With the increasingly sensitive nature of information transmitted over wireless networks, privacy and secrecy mechanisms have naturally become an integral part of new protocols and standards. While identified weaknesses of previous generation wireless protocols are typically addressed with the rollout of the next generation, challenges constantly emerge that must be proactively addressed. For instance, while 5G systems have addressed some of the security weaknesses identified in 4G systems, the attack surface of 5G networks has increased because of the heterogeneity of devices and the larger number of use cases [48], as exemplified by the growth of machine-to-machine communications [19]. Consequently, security has yet again already been identified as one of the main challenges that 6G networks must address [72].
Several security solutions have been considered to provide full-stack security, including lightweight cryptography for Internet of Things (IoT) devices [61], the use of post-quantum cryptography [3, 72], and physical-layer security (PLS) [11, 45], which has again re-emerged as a possible technology [32, 38, 49, 66, 74]. The key concept behind PLS is to exploit the random imperfections inherent to wireless channels and devices (noise, interference) to provide, e.g., secrecy or authentication, using physical-layer signal processing and coding algorithms [11, 56, 68]. While PLS may certainly not solve all 6G security challenges in isolation, its main benefits are (i) to provide a concrete framework in which security can be quantified, e.g., through the notion of secrecy capacity [68]; (ii) to treat security on par with other system-level metrics, such as power consumption, throughput, and latency, at the design stage; (iii) to reduce the attack surface at the physical layer by making eavesdropping extremely costly, if not ineffective; and (iv) to seamlessly integrate with security mechanisms in the upper layers of the protocol stack. In particular, ensuring confidentiality for ultralow-latency communications is a known challenge [1, 54] that PLS could help tackle [15, 58].
PLS was already discussed in the context of 5G networks [35, 66], and one should recognize that, with the exception of niche applications and use cases [73], PLS has not had much impact on deployed systems. This state of affairs can be attributed to a multitude of factors, both technological and conceptual, ranging from scientific challenges related to the foundation of PLS itself (e.g., how do we characterize and learn a passive eavesdropper's channel?) to technological hurdles (e.g., how do we justify integrating new codes at the physical layer of a standard?). Nevertheless, 6G promises new unique features that may finally offer the opportunity to push PLS into widely deployed systems [16, 45]. In particular, the integration of sensing and communication, especially as it relates to enhancing the localization of devices, and the push toward higher frequencies in the mmWave region are offering new avenues to strengthen the case of PLS.
The objective of this chapter is twofold. First, we will review the seminal coding ideas behind PLS, which have been refined over the last two decades to provide a strong basis for discussing secrecy in a principled manner. Second, we will discuss how these principles may be used in the more specific context of 6G systems, with an eye toward engineering channels, developing dedicated hardware, and exploiting channel knowledge for security. Given the breadth of literature on the topic, this chapter does not do justice to many creative ideas, in particular those involving PLS in the context of networks of many devices for which the reader is referred to tutorial articles [46, 51, 66, 71]. The focus of the chapter is on point-to-point links, for they still capture the essence of the challenges that remain to address and the opportunities that have emerged and might represent the realistic use cases for which PLS could be deployed at scale.
1.1 Coding Mechanisms
The appeal of (PLS) can be largely attributed to the early work of Wyner [68], Csiszár and Körner [21], Ahlswede and Csiszár [2], and Maurer [43], that first established and analyzed the notion of secrecy capacity and secret-key capacity. We defer to Section 1.2 for exact definitions, suffice to say for now that these definitions are the counterparts of the traditional notion of channel capacity and that they quantify the maximum rate of information that can be transmitted or extracted reliably and confidentially over a channel that includes an eavesdropping adversary. While secrecy capacity and secret-key capacity therefore provide system-level metrics that can be optimized as a function of channel parameters to understand how much secrecy can be achieved in a network, the ability to operationalize them is fundamentally tied to the ability to design specific coding schemes to extract or encode information in signal. Said differently, in the same way that the notion of channel capacity is useful because good error-control codes exist, secrecy and secret-key capacity are useful because good secrecy codes exist. The objective of this section is to introduce four coding operations that shall enable PLS by providing operational meaning to what it means to enforce secrecy in Section 1.2.
1.1.1 Channel Coding
The problem of channel coding is illustrated in Figure 1.1. The objective consists in transmitting a uniformly distributed messages over uses of a discrete memoryless channel with known transition probability by encoding the message into a coded sequence . The set of coded sequences is called the codebook while is called the blocklength of the code. Upon receiving the corrupted signal , the receiver attempts construct a correct estimate of using its knowledge of the channel and the code. The performance of channel coding may be measured in terms of the rate of transmission and the probability of decoding error .
The seminal result established by Shannon [55] is that, asymptotically, reliable communication is possible as long as the rate does not exceed a channel-dependent quantity called the channel capacity. We state this result more formally as follows.
Theorem 1.1 Given a discrete memoryless channel with known transition probability , a distribution and any , there exists a blocklength and an encoder/decoder pair such that and where is the mutual information between the random variables and with joint distribution . The quantity is called the channel capacity since no higher such constant can be found.
Specific instances of such codes can be designed using low-density parity-check codes [24, 33, 34] or polar codes [4].
Figure 1.1 Channel coding over a discrete memoryless channel.
1.1.2 Soft Covering
The operation of channel coding can be interpreted as introducing structure in coded sequences that is resilient to the corruption of the noisy channel. A lesser known coding operation over channels consists in introducing structure in coded sequences that disappear when corrupted by noise. Formally, this coding operation called soft covering is illustrated in Figure 1.2. Consider a random variable with distribution transmitted over a discrete memoryless channel with known transition probability . The output of the channel is a new random variable with distribution obtained by taking the marginal of . Instead of transmitting the random variable , one can instead ask whether one can approximately simulate transmissions of the random variable using instead a uniformly distributed message encoded into sequences of length . The intuition is that -coded sequences might be sufficient to approximately cover all possible realizations of i.i.d. realizations of the random variable . The performance of soft covering may be measured in terms of the rate of transmission and the relative entropy , where is the distribution induced by the random choice of coded sequences while is the -fold product distribution of .
The fundamental result of soft covering, first identified by Wyner [67] but studied and refined later on by others [22, 26, 29, 30, 65], is that and are virtually indistinguishable as long as the rate does not fall below a quantity called the channel resolvability. We state this result more formally below.
Theorem 1.2 Given a discrete memoryless channel with known transition probability , a distribution , and any , there exists a blocklength and an encoder such that and , where is the mutual information between the random variables and with joint distribution . The quantity is called the channel...
