Next-Generation Systems and Secure Computing

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Next-Generation Systems and Secure Computing

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  • 製本 Hardcover:ハードカバー版/ページ数 480 p.
  • 言語 ENG
  • 商品コード 9781394228263
  • DDC分類 005.8

Full Description

Next-Generation Systems and Secure Computing is essential for anyone looking to stay ahead in the rapidly evolving landscape of technology. It offers crucial insights into advanced computing models and their security implications, equipping readers with the knowledge needed to navigate the complex challenges of today's digital world.

The development of technology in recent years has produced a number of scientific advancements in sectors like computer science. The advent of new computing models has been one particular development within this sector. New paradigms are always being invented, greatly expanding cloud computing technology. Fog, edge, and serverless computing are examples of these revolutionary advanced technologies. Nevertheless, these new approaches create new security difficulties and are forcing experts to reassess their current security procedures. Devices for edge computing aren't designed with the same IT hardware protocols in mind. There are several application cases for edge computing and the Internet of Things (IoT) in remote locations. Yet, cybersecurity settings and software upgrades are commonly disregarded when it comes to preventing cybercrime and guaranteeing data privacy.

Next-Generation Systems and Secure Computing compiles cutting-edge studies on the development of cutting-edge computing technologies and their role in enhancing current security practices. The book will highlight topics like fault tolerance, federated cloud security, and serverless computing, as well as security issues surrounding edge computing in this context, offering a thorough discussion of the guiding principles, operating procedures, applications, and unexplored areas of study. Next-Generation Systems and Secure Computing is a one-stop resource for learning about the technology, procedures, and individuals involved in next-generation security and computing.

Contents

Preface xxi

1 Yet Another Move Towards Securing Video Using Sudoku-Fernet 1
Sunanda Jana, Swarnajit Bhattacharya, Mrinmoy Sen, Abhinandan Khan, Arnab Kumar Maji and Rajat Kumar Pal

1.1 Introduction 1

1.2 Literature Survey 6

1.3 Proposed Methodology 8

1.4 Result Analysis 12

1.5 Computational Complexity 14

1.6 Conclusions 15

References 15

2 Watermarking: Characteristics, Methods, and Evaluation 17
Soumitra Roy and Bappaditya Chakraborty

2.1 Introduction 18

2.2 Watermark Definition 20

2.3 Properties of Watermarking 22

2.4 Categorization of Watermarking 25

2.5 Attacks on Watermarking 29

2.6 Chapter Summary 32

References 32

3 A Comprehensive Study on Deep Learning and Artificial Intelligence for Malware Analysis 39
Tukkappa Gundoor and Sridevi

3.1 Introduction 40

3.2 The Evolving Landscape of Malware Threats 40

3.3 The Role of Deep Learning and AI in Enhancing Cybersecurity 42

3.4 Deep Learning Models for Malware Analysis 45

3.5 AI Techniques in Malware Analysis 50

3.6 Challenges and Limitations in Malware Family Classification 51

3.7 Future Directions 54

References 55

4 Transmit Texts Covertly Using Trigonometric Functions and Pythagorean Theorem 61
Nagadevi Bala Nagaram, R. Narmada Devi and S. Karpagam

4.1 Introduction 62

4.2 Mainstream Definition 69

4.3 Description of the Work 73

4.4 Algorithm for Decryption 75

4.5 Conclusion 76

References 76

5 Exploring the Synergy of Cybersecurity and Blockchain: Strengthening Digital Defenses 79
Mohan Kumar Dehury, Bhabendu Kumar Mohanta, Manorama Patnaik, Biresh Kumar and Purushottam Kumar

5.1 Introduction 80

5.2 Blockchain Infrastructure 81

5.3 Literature Review 86

5.4 Cybersecurity Fundamentals 87

5.5 Synergies Between Blockchain and Cybersecurity 93

5.6 Applications of Blockchain and Cybersecurity 94

5.7 Challenges and Considerations 95

5.8 Future Directions and Innovations 97

5.9 Conclusion 98

References 99

6 Protecting in the Digital Age: A Comprehensive Examination of Cybersecurity and Legal Implications 105
Nazeer Shaik, B. Hari Chandana, P. Chitralingappa and C. Sasikala

6.1 Introduction 106

6.2 First-Order Heading 107

6.3 Data Protection and Privacy Laws 111

6.4 Intellectual Property Rights in Cyberspace 116

6.5 Cybersecurity Regulations and Compliance 117

6.6 Cybersecurity Incident Response and Reporting 117

6.7 International Laws and Jurisdiction in Cybersecurity 118

6.8 Liability and Responsibility in Cybersecurity 122

6.9 Government Surveillance and Cybersecurity 123

6.10 Cybersecurity and Employment Law 124

6.11 Cybersecurity and E-Commerce 126

6.12 Emerging Legal Issues in Cybersecurity 127

6.13 Result 131

6.14 Conclusion 132

References 133

7 A Novel Non-Orthogonal Multiple Access Scheme for Next Generation Millimeter-Wave 5G Communications 137
Udayakumar Easwaran and Krishnaveni Vellingiri

7.1 Introduction 138

7.2 Related Works 141

7.3 MIMO-NOMA Systems 143

7.4 Phase Noise 150

7.5 Results and Discussion 153

7.6 Conclusion 156

References 156

8 Generation of Key Predistribution Scheme Applying Quasi-Symmetric Designs and Bent Functions in the Wireless Sensor Network 159
Debashis Ghosh

8.1 Introduction 160

8.2 Background 163

8.3 Our Proposed Scheme 178

8.4 Conclusion 182

References 183

9 Enhanced Security Measures Within the ITS Infrastructure Through the Application of Machine Learning Algorithms for Anomaly Detection 187
Shiplu Das, Soumi De, Ananya Ghosh, Sovraj Dey and Tania Bhattacharjee

9.1 Introduction 188

9.2 Literature Review 190

9.3 Proposed Work 197

9.4 Methodology Analysis and Discussion 199

9.5 Conclusion 202

References 203

10 The Impact of Distributed Ledger in IoT: A Comprehensive Overview 205
Rick Hore, Rishav Dan, Abhijit Sarkar and Sabyasachi Samanta

10.1 Introduction 206

10.2 Related Work 212

10.3 The Potential of DTL in IoT Application 215

10.4 Current Use Cases of IoT and DLT 218

10.5 Opportunities and Challenges of Integrating DLT with IoT 220

10.6 The Future of DLT in IoT Ecosystems 222

10.7 Conclusion 224

References 225

11 A Cryptographic Technique Using Chemicals and Graphs 229
Kala Raja Mohan, Nagadevi Bala Nagaram, R. Narmada Devi, Regan Murugesan and Subashini Chandrasekar

11.1 Introduction 230

11.2 Standard Definitions 231

11.3 Periodic Table 232

11.4 Coding Table with Chemical Elements 232

11.5 Encryption Algorithm 233

11.6 Encryption Process—Example 233

11.7 Algorithm for Decryption 235

11.8 Decryption Process-Example 235

11.9 Conclusion 236

References 236

12 Federated Learning: A Secure Distributed Machine Learning Approach for IoT Technology 239
Rituparna Saha and Amit Biswas

12.1 Introduction 240

12.2 Categorization of FL 243

12.3 Data Availability 244

12.4 Federated Learning Training Approaches 244

12.5 Key Research Directions Related to FL 245

12.6 Application Areas of FL 246

12.7 Conclusion 250

References 250

13 Security Analysis for Mobile Crowdsensing Scheme by Predicting Vehicle Mobility Using Deep Learning Algorithm 257
Monojit Manna, Arpan Adhikary and Sima Das

13.1 Introduction 258

13.2 Related Work 259

13.3 System Model 261

13.4 Model of Threat in Mobile Crowdsensing 262

13.5 DL-Based Authentication 264

13.6 Dl-Based Privacy Protection 265

13.7 False Sensing Countermeasures Based on dl 267

13.8 Dl-Based Detection of Intrusion 267

13.9 The DLMV Approach's Design 269

13.10 Experimental Result 272

13.11 Conclusion 273

References 274

14 A Study on Protection of Multimedia System Contents Using a Biometric-Based Encryption Technique 277
Pinaki Pratim Acharjya, Santanu Koley, Subhabrata Barman, Subhankar Joardar and Jayeeta Majumder

14.1 Introduction 277

14.2 Literature Survey 281

14.3 Multimedia Content Protection 283

14.4 Encryption/Decryption in Biometrics 284

14.5 The Process 287

14.6 Experimental Results 289

14.7 Conclusion 290

References 290

15 Deep Learning Algorithms for Detecting Network Attacks—An Overview 293
R. Mythili and A.S. Aneetha

15.1 Introduction 294

15.2 Technologies of Network Security 296

15.3 Network Attacks 299

15.4 Deep Learning Approaches 302

15.5 Models of IDS 311

15.6 IDS Datasets 312

15.7 Result Analysis 314

15.8 Evaluation Metrics 315

15.9 Conclusion 320

References 321

16 Deep Learning Techniques for Detection of Fake News in Social Media with Huge Data 325
Namratha M., Rajeshwari B. S. and Jyothi S. Nayak

16.1 Introduction 326

16.2 Related Work 329

16.3 Proposed Work 332

16.4 Results and Discussion 337

16.5 Conclusion 342

16.6 Future Work 343

References 344

17 A Secure IoT-Based Heart Rate Monitoring and Analyzing System 347
Soumya Roy, Rajib Manna, Sabyasachi Samanta, Moumita Sahoo and Somak Karan

17.1 Introduction 348

17.2 Literature Review 353

17.3 Methodology 355

17.4 Result Analysis 369

17.5 Conclusion 376

References 377

18 A Secure IoT-Based Approach for Smart Irrigation System Using an Arduino Uno Microcontroller 379
Nitesh Kumar, Soumen Ghosh, Sabyasachi Samanta, Abhijit Sarkar and Priyatosh Jana

18.1 Introduction 380

18.2 Literature Review 384

18.3 Methodology 388

18.4 Result Analysis 395

18.5 Conclusion 396

18.6 Future Aspect 396

Acknowledgments 397

References 397

19 Machine Learning Applications, Challenges, and Securities for Remote Healthcare: A Systematic Review 401
Arpan Adhikary, Sima Das, Asit Kumar Nayek, Monojit Manna and Rabindranath Sahu

19.1 Introduction 402

19.2 Definition of Remote Monitoring of Patients 403

19.3 Difference Between the Terminologies "Remote Health Care" and "Remote Healthcare" 404

19.4 Components of the Remote Healthcare System 404

19.5 Benefits of Remote Healthcare 405

19.6 Challenges in the Remote Healthcare System 406

19.7 Application Areas of Machine Learning in the Remote Healthcare System 406

19.8 The Advantage of Remote Monitoring System 408

19.9 Important Features and Factors of the Remote Monitoring System 409

19.10 Sensors Needed for the Wireless Body Area Network (wban) 411

19.12 Machine Learning Solution for Remote Monitoring 413

19.13 Internet of Things Solution for Remote Monitoring 414

19.14 Security Solution for the Remote Monitoring 416

19.15 Conclusion 416

References 417

20 Enhancing Video Steganography Security for Cross-Platform Applications: A Focus on High-Definition Formats and Streaming Environments 421
Santanu Koley and Ankur Kumar

20.1 Introduction 422

20.2 Video Steganography 422

20.3 The Compressed Domain 422

20.4 Coding Concepts 423

20.5 Temporal Model 424

20.6 Macroblocks Motion Estimation 425

20.7 Steganalysis 425

20.8 Cryptography 428

20.9 Steganographic Encoder 435

20.10 Conclusion 437

20.11 Future Work 438

References 438

Index 441

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