Produktbild: Evolution and Applications of Quantum Computing

Evolution and Applications of Quantum Computing

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.06.2023

Herausgeber

Sachi Nandan Mohanty + weitere

Verlag

John Wiley & Sons Inc

Seitenzahl

352

Maße (L/B/H)

25/15/1,5 cm

Gewicht

739 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-90486-1

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.06.2023

Herausgeber

Verlag

John Wiley & Sons Inc

Seitenzahl

352

Maße (L/B/H)

25/15/1,5 cm

Gewicht

739 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-90486-1

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Evolution and Applications of Quantum Computing
  • Preface xvii

    1 Introduction to Quantum Computing 1
    V. Padmavathi, C. N. Sujatha, V. Sitharamulu, K. Sudheer Reddy and A. Mallikarjuna Reddy

    1.1 Quantum Computation 2

    1.2 Importance of Quantum Mechanics 2

    1.3 Security Options in Quantum Mechanics 2

    1.4 Quantum States and Qubits 3

    1.5 Quantum Mechanics Interpretation 4

    1.6 Quantum Mechanics Implementation 4

    1.6.1 Photon Polarization Representation 4

    1.7 Quantum Computation 6

    1.7.1 Quantum Gates 7

    1.8 Comparison of Quantum and Classical Computation 11

    1.9 Quantum Cryptography 12

    1.10 Qkd 12

    1.11 Conclusion 12

    References 13

    2 Fundamentals of Quantum Computing and Significance of Innovation 15
    Swapna Mudrakola, Uma Maheswari V., Krishna Keerthi Chennam and MVV Prasad Kantidpudi

    2.1 Quantum Reckoning Mechanism 16

    2.2 Significance of Quantum Computing 16

    2.3 Security Opportunities in Quantum Computing 16

    2.4 Quantum States of Qubit 17

    2.5 Quantum Computing Analysis 17

    2.6 Quantum Computing Development Mechanism 18

    2.7 Representation of Photon Polarization 18

    2.8 Theory of Quantum Computing 20

    2.9 Quantum Logical Gates 21

    2.9.1 I-Qubit GATE 21

    2.9.2 Hadamard-GATE 22

    2.9.3 NOT_GATE_QUANTUM or Pauli_X-GATE 22

    2.9.3.1 Pauli_Y-GATE 23

    2.9.3.2 Pauli_Z-GATE 23

    2.9.3.3 Pauli_S-Gate 23

    2.9.4 Two-Qubit GATE 24

    2.9.5 Controlled NOT(C-NOT) 24

    2.9.6 The Two-Qubits are Swapped Using SWAP_GATE 24

    2.9.7 C-Z-GATE (Controlled Z-GATE) 24

    2.9.8 C-P-GATE (Controlled-Phase-GATE) 25

    2.9.9 Three-Qubit Quantum GATE 25

    2.9.9.1 GATE: Toffoli Gate 25

    2.9.10 F-C-S GATE (Fredkin Controlled Swap-GATE) 26

    2.10 Quantum Computation and Classical Computation Comparison 27

    2.11 Quantum Cryptography 27

    2.12 Quantum Key Distribution - QKD 27

    2.13 Conclusion 28

    References 28

    3 Analysis of Design Quantum Multiplexer Using CSWAP and Controlled-R Gates 31
    Virat Tara, Navneet Sharma, Pravindra Kumar and Kumar Gautam

    3.1 Introduction 32

    3.2 Mathematical Background of Quantum Circuits 34

    3.2.1 Hadamard Gate 34

    3.2.2 CSWAP Gates 35

    3.2.3 Controlled-R Gates 36

    3.3 Methodology of Designing Quantum Multiplexer (QMUX) 36

    3.3.1 QMUX Using CSWAP Gates 36

    3.3.1.1 Generalization 37

    3.3.2 QMUX Using Controlled-R Gates 37

    3.4 Analysis and Synthesis of Proposed Methodology 39

    3.5 Complexity and Cost of Quantum Circuits 41

    3.6 Conclusion 42

    References 42

    4 Artificial Intelligence and Machine Learning Algorithms in Quantum Computing Domain 45
    Syed Abdul Moeed, P. Niranjan and G. Ashmitha

    4.1 Introduction 46

    4.1.1 Quantum Computing Convolutional Neural Network 51

    4.2 Literature Survey 52

    4.3 Quantum Algorithms Characteristics Used in Machine Learning Problems 58

    4.3.1 Minimizing Quantum Algorithm 58

    4.3.2 K-NN Algorithm 58

    4.3.3 K-Means Algorithm 60

    4.4 Tree Tensor Networking 61

    4.5 TNN Implementation on IBM Quantum Processor 62

    4.6 Neurotomography 62

    4.7 Conclusion and Future Scope 63

    References 64

    5 Building a Virtual Reality-Based Framework for the Education of Autistic Kids 67
    Kanak Pandit, Aditya Mogare, Achal Shah, Prachi Thete and Megharani Patil

    5.1 Introduction 68

    5.2 Literature Review 71

    5.3 Proposed Work 74

    5.3.1 Methodology 74

    5.3.2 Work Flow of Neural Style Transfer 75

    5.3.3 A-Frame 75

    5.3.3.1 Setting Up the Virtual World and Adding Components 75

    5.3.3.2 Adding Interactivity Through Raycasting 76

    5.3.3.3 Animating the Components 77

    5.3.4 Neural Style Transfer 78

    5.3.4.1 Choosing the Content and Styling Image 79

    5.3.4.2 Image Preprocessing and Generation of a Random Image 79

    5.3.4.3 Model Design and Extraction of Content and Style 81

    5.3.4.4 Loss Calculation 81

    5.3.4.5 Model Optimization 84

    5.4 Evaluation Metrics 86

    5.5 Results 89

    5.5.1 A-Frame 89

    5.5.2 Neural Style Transfer 90

    5.6 Conclusion 90

    References 91

    6 Detection of Phishing URLs Using Machine Learning and Deep Learning Models Implementing a URL Feature Extractor 93
    Abishek Mahesh, Prithvi Seshadri, Shruti Mishra and Sandeep Kumar Satapathy

    6.1 Introduction 94

    6.2 Related Work 94

    6.3 Proposed Model 95

    6.3.1 URL Feature Extractor 95

    6.3.2 Dataset 103

    6.3.3 Methodologies 104

    6.3.3.1 AdaBoost Classifier 105

    6.3.3.2 Gradient Boosting Classifier 105

    6.3.3.3 K-Nearest Neighbors 105

    6.3.3.4 Logistic Regression 106

    6.3.3.5 Artificial Neural Networks 106

    6.3.3.6 Support Vector Machines (SVM) 107

    6.3.3.7 Naïve Bayes Classifier 107

    6.4 Results 109

    6.5 Conclusions 109

    References 109

    7 Detection of Malicious Emails and URLs Using Text Mining 111
    Heetakshi Fating, Aditya Narawade, Sandeep Kumar Satapathy and Shruti Mishra

    7.1 Introduction 112

    7.2 Related Works 112

    7.3 Dataset Description 114

    7.4 Proposed Architecture 115

    7.5 Methodology 116

    7.5.1 Methodology for the URL Dataset 116

    7.5.2 Methodology for the Email Dataset 118

    7.5.2.1 Overcoming the Overfitting Problem 118

    7.5.2.2 Tokenization 119

    7.5.2.3 Applying Machine Learning Algorithms 119

    7.5.3 Detecting Presence of Malicious URLs in Otherwise Non-Malicious Emails 119

    7.5.3.1 Preparation of Dataset 119

    7.5.3.2 Creation of Features 120

    7.5.3.3 Applying Machine Learning Algorithms 120

    7.6 Results 120

    7.6.1 URL Dataset 120

    7.6.2 Email Dataset 121

    7.6.3 Final Dataset 121

    7.7 Conclusion 122

    References 122

    8 Quantum Data Traffic Analysis for Intrusion Detection System 125
    Anshul Harish Khatri, Vaibhav Gadag, Simrat Singh, Sandeep Kumar Satapathy and Shruti Mishra

    8.1 Introduction 126

    8.2 Literature Overview 127

    8.3 Methodology 129

    8.3.1 Autoviz 129

    8.3.2 Dataset 132

    8.3.3 Proposed Models 132

    8.3.3.1 Decision Tree 135

    8.3.3.2 Random Forest Classifier Algorithm 136

    8.3.3.3 AdaBoost Classifier 136

    8.3.3.4 Ridge Classifier 137

    8.3.3.5 Logistic Regression 137

    8.3.3.6 SVM-Linear Kernel 138

    8.3.3.7 Naive Bayes 138

    8.3.3.8 Quadratic Discriminant Analysis 139

    8.4 Results 140

    8.5 Conclusion 141

    References 142

    9 Quantum Computing in Netnomy: A Networking Paradigm in e-Pharmaceutical Setting 145
    Sarthak Dash, Sugyanta Priyadarshini, Sachi Nandan Mohanty, Sukanya Priyadarshini and Nisrutha Dulla

    9.1 Introduction 146

    9.2 Discussion 148

    9.2.1 Exploring Market Functioning via Quantum Network Economy 148

    9.2.1.1 Internal Networking Marketing 149

    9.2.1.2 Layered Marketing 149

    9.2.1.3 Role of Marketing in Pharma Network Organizations 150

    9.2.1.4 Role of Marketing in Vertical Networking Organizations 152

    9.2.1.5 Generic e-Commerce Entity Model in Pharmaceutical Industry 153

    9.2.2 Analyzing the Usability of Quantum Netnomics in Attending Economic Development 154

    9.2.2.1 Theory of 4Ps in Pharma Marketing mix 155

    9.2.2.2 Buying Behavior of the e-Consumers 156

    9.2.2.3 Maintaining of Privacy and Security via Quantum Technology in e-Structure 157

    9.2.2.4 Interface Influencing Sales 157

    9.3 Results 158

    9.4 Conclusion 159

    References 159

    10 Machine Learning Approach in the Indian Service Industry: A Case Study on Indian Banks 163
    Pragati Priyadarshinee

    10.1 Introduction 163

    10.2 Literature Survey 164

    10.3 Experimental Results 170

    10.4 Conclusion 172

    References 172

    11 Accelerating Drug Discovery with Quantum Computing 175
    Mahesh V. and Shimil Shijo

    11.1 Introduction 175

    11.2 Working Nature of Quantum Computers 176

    11.3 Use Cases of Quantum Computing in Drug Discovery 178

    11.4 Target Drug Identification and Validation 179

    11.5 Drug Discovery Using Quantum Computers is Expected to Start by 2030 179

    11.6 Conclusion 180

    References 181

    12 Problems and Demanding Situations in Traditional Cryptography: An Insistence for Quantum Computing to Secure Private Information 183
    D. DShivaprasad, Mohamed Sirajudeen Yoosuf, P. Selvaramalakshmi, Manoj A. Patil and Dasari Promod Kumar

    12.1 Introduction to Cryptography 184

    12.1.1 Confidentiality 184

    12.1.2 Authentication 185

    12.1.3 Integrity 185

    12.1.4 Non-Repudiation 186

    12.2 Different Types of Cryptography 186

    12.2.1 One-Way Processing 186

    12.2.1.1 Hash Function (One-Way Processing) 186

    12.2.2 Two-Way Processing 187

    12.2.2.1 Symmetric Cryptography 188

    12.2.2.2 Asymmetric Cryptography 189

    12.2.3 Algorithms Types 190

    12.2.3.1 Stream Cipher 190

    12.2.3.2 Block Cipher 191

    12.2.4 Modes of Algorithm 192

    12.2.4.1 Cipher Feedback Mode 192

    12.2.4.2 Output Feedback Mode 192

    12.2.4.3 Cipher Block Chaining Mode 192

    12.2.4.4 Electronic Code Book 192

    12.3 Common Attacks 193

    12.3.1 Passive Attacks 193

    12.3.1.1 Traffic Analysis 193

    12.3.1.2 Eavesdropping 194

    12.3.1.3 Foot Printing 195

    12.3.1.4 War Driving 195

    12.3.1.5 Spying 195

    12.3.2 Active Attacks 196

    12.3.2.1 Denial of Service 196

    12.3.2.2 Distributed Denial of Service (DDOS) 197

    12.3.2.3 Message Modification 197

    12.3.2.4 Masquerade 197

    12.3.2.5 Trojans 198

    12.3.2.6 Replay Attacks 199

    12.3.3 Programming Weapons for the Attackers 199

    12.3.3.1 Dormant Phase 200

    12.3.3.2 Propagation Phase 200

    12.3.3.3 Triggering Phase 201

    12.3.3.4 Execution Phase 201

    12.4 Recent Cyber Attacks 201

    12.5 Drawbacks of Traditional Cryptography 203

    12.5.1 Cost and Time Delay 203

    12.5.2 Disclosure of Mathematical Computation 203

    12.5.3 Unsalted Hashing 204

    12.5.4 Attacks 204

    12.6 Need of Quantum Cryptography 204

    12.6.1 Quantum Mechanics 204

    12.7 Evolution of Quantum Cryptography 205

    12.8 Conclusion and Future Work 205

    References 205

    13 Identification of Bacterial Diseases in Plants Using Re-Trained Transfer Learning in Quantum Computing Environment 207
    Sri Silpa Padmanabhuni, B. Srikanth Reddy, A. Mallikarjuna Reddy and K. Sudheer Reddy

    13.1 Introduction 208

    13.2 Literature Review 218

    13.3 Proposed Methodology 220

    13.3.1 SVM Classifier 222

    13.3.2 Random Forest to Classify the Rice Leaf 223

    13.3.2.1 Image Pre-Processing 223

    13.3.2.2 Feature Extraction 223

    13.3.2.3 Classification 224

    13.4 Experiment Results 226

    Conclusion 230

    References 230

    14 Quantum Cryptography 233
    Salma Fauzia

    14.1 Fundamentals of Cryptography 234

    14.2 Principle of Quantum Cryptography 237

    14.2.1 Quantum vs. Conventional Cryptography 237

    14.3 Quantum Key Distribution Protocols 238

    14.3.1 Overview and BB84 Protocol 238

    14.3.2 The B92 Protocol 240

    14.3.3 E91 Protocol 241

    14.3.4 SARG04 Protocol 243

    14.4 Impact of the Sifting and Distillation Steps on the Key Size 243

    14.5 Cryptanalysis 246

    14.6 Quantum Key Distribution in the Real World 247

    References 248

    15 Security Issues in Vehicular Ad Hoc Networks and Quantum Computing 249
    B. Veera Jyothi, L. Suresh Kumar and B. Surya Samantha

    15.1 Introduction 250

    15.2 Overview of VANET Security 250

    15.2.1 Security of VANET 250

    15.2.2 Attacks are Classified 251

    15.3 Architectural and Systematic Security Methods 252

    15.3.1 Solutions for Cryptography 252

    15.3.2 Framework for Trust Groups 252

    15.3.3 User Privacy Security System Based on ID 253

    15.4 Suggestions on Particular Security Challenges 254

    15.4.1 Content Delivery Integrity Metrics 254

    15.4.2 Position Detection 254

    15.4.3 Protective Techniques 255

    15.5 Quantum Computing in Vehicular Networks 257

    15.5.1 Securing Automotive Ecosystems: A Challenge 257

    15.5.2 Generation of Quantum Random Numbers (QRNG) 258

    15.6 Quantum Key Transmission (QKD) 258

    15.7 Quantum Internet - A Future Vision 259

    15.7.1 Quantum Internet Applications 259

    15.7.2 Application Usage-Based Categorization 260

    15.8 Conclusions 262

    References 263

    16 Quantum Cryptography with an Emphasis on the Security Analysis of QKD Protocols 265
    Radhika Kavuri, Santhosh Voruganti, Sheena Mohammed, Sucharitha Inapanuri and B. Harish Goud

    16.1 Introduction 266

    16.2 Basic Terminology and Concepts of Quantum Cryptography 267

    16.2.1 Quantum Cryptography and Quantum Key Distribution 267

    16.2.2 Quantum Computing and Quantum Mechanics 267

    16.2.3 Post-Quantum Cryptography 267

    16.2.4 Quantum Entanglement 267

    16.2.5 Heisenberg's Uncertainty Principle 268

    16.2.6 Qubits 268

    16.2.7 Polarization 269

    16.2.8 Traditional Cryptography vs. Quantum Cryptography 269

    16.3 Trends in Quantum Cryptography 270

    16.3.1 Global Quantum Key Distribution Links 271

    16.3.2 Research Statistics on Quantum Cryptography 273

    16.4 An Overview of QKD Protocols 274

    16.4.1 Introduction to the Prepare-and-Measure Protocols 275

    16.4.2 The BB84 Protocol 275

    16.4.3 B92 Protocol 278

    16.4.4 Six State Protocol (SSP) 278

    16.4.5 SARG04 Protocol 279

    16.4.6 Introduction to the Entanglement-Based Protocols 280

    16.4.7 The E91 Protocol 280

    16.4.8 The BBM92 Protocol 280

    16.5 Security Concerns in QKD 282

    16.6 Future Research Foresights 284

    16.6.1 Increase in Bit Rate 284

    16.6.2 Longer Distance Coverage 284

    16.6.3 Long Distance Quantum Repeaters 285

    16.6.4 Device Independent Quantum Cryptography 285

    16.6.5 Development of Tools for Simulation and Measurements 285

    16.6.6 Global Quantum Communication Network 285

    16.6.7 Integrated Photonic Spaced QKD 285

    16.6.8 Quantum Teleportation 286

    References 286

    17 Deep Learning-Based Quantum System for Human Activity Recognition 289
    Shoba Rani Salvadi, Narsimhulu Pallati and Madhuri T.

    17.1 Introduction 290

    17.2 Related Works 292

    17.3 Proposed Scheme 293

    17.3.1 Datasets Description 294

    17.3.2 Pre-Processing 294

    17.3.3 Feature Extraction 295

    17.3.4 Preliminaries 295

    17.3.4.1 Quantum Computing 296

    17.3.4.2 Convolutional Neural Networks 296

    17.3.5 Proposed ORQC-CNN Model 296

    17.3.5.1 Quantum Convolutional Layer 297

    17.3.5.2 Convolutional Layer 299

    17.3.5.3 Max-Pooling Layer 299

    17.3.5.4 Fully Connected Layer 299

    17.3.6 Parameter Selection Using Artificial Gorilla Troops Optimization Algorithm (AGTO) 300

    17.3.6.1 Exploration Phase 301

    17.3.6.2 Exploitation Phase 302

    17.3.6.3 Follow the Silverback 303

    17.3.6.4 Competition for Adult Females 303

    17.3.7 Computational Difficulty 304

    17.4 Results and Discussion 304

    17.4.1 Performance Measure 305

    17.4.2 Performance Analysis of Dataset 1 306

    17.4.3 Performance Analysis of Dataset 2 307

    17.4.4 Comparison 308

    17.5 Conclusion 309

    References 309

    18 Quantum Intelligent Systems and Deep Learning 313
    Bhagaban Swain and Debasis Gountia

    18.1 Introduction 313

    18.2 Quantum Support Vector Machine 315

    18.3 Quantum Principal Component Analysis 318

    18.4 Quantum Neural Network 319

    18.5 Variational Quantum Classifier 321

    18.6 Conclusion 323

    References 323

    Index 327