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.