Evolution and Applications of Quantum Computing

EVOLUTION and APPLICATIONS of QUANTUM COMPUTING The book is about the Quantum Model replacing traditional computing’s classical model and gives a state-of-the-art technical overview of the current efforts to develop quantum computing and applications for Industry 4.0. A holistic approach to the revolutionary world of quantum computing is presented in this book, which reveals valuable insights into this rapidly emerging technology. The book reflects the dependence of quantum computing on the physical phenomenon of superposition, entanglement, teleportation, and interference to simplify difficult mathematical problems which would have otherwise taken years to derive a definite solution for. An amalgamation of the information provided in the multiple chapters will elucidate the revolutionary and riveting research being carried out in the brand-new domain encompassing quantum computation, quantum information and quantum mechanics. Each chapter gives a concise introduction to the topic. The book comprises 18 chapters and describes the pioneering work on the interaction between artificial intelligence, machine learning, and quantum computing along with their applications and potential role in the world of big data. Subjects include: Combinational circuits called the quantum multiplexer with secured quantum gate (CSWAP); Detecting malicious emails and URLs by using quantum text mining algorithms to distinguish between phishing and benign sites; Quantum data traffic analysis for intrusion detection systems; Applications of quantum computation in banking, netnomy and vehicular ad-hoc networks, virtual reality in the education of autistic children, identifying bacterial diseases and accelerating drug discovery; The critical domain of traditional classical cryptography and quantum cryptography. Audience The book will be very useful for researchers in computer science, artificial intelligence and quantum physics as well as students who want to understand the history of quantum computing along with its applications and have a technical state-of-the-art overview. Cover Title Page Copyright Page Contents Preface Chapter 1 Introduction to Quantum Computing 1.1 Quantum Computation 1.2 Importance of Quantum Mechanics 1.3 Security Options in Quantum Mechanics 1.4 Quantum States and Qubits 1.5 Quantum Mechanics Interpretation 1.6 Quantum Mechanics Implementation 1.6.1 Photon Polarization Representation 1.7 Quantum Computation 1.7.1 Quantum Gates 1.8 Comparison of Quantum and Classical Computation 1.9 Quantum Cryptography 1.10 QKD 1.11 Conclusion References Chapter 2 Fundamentals of Quantum Computing and Significance of Innovation 2.1 Quantum Reckoning Mechanism 2.2 Significance of Quantum Computing 2.3 Security Opportunities in Quantum Computing 2.4 Quantum States of Qubit 2.5 Quantum Computing Analysis 2.6 Quantum Computing Development Mechanism 2.7 Representation of Photon Polarization 2.8 Theory of Quantum Computing 2.9 Quantum Logical Gates 2.9.1 I-Qubit GATE 2.9.2 Hadamard-GATE 2.9.3 NOT_GATE_QUANTUM or Pauli_X-GATE 2.9.3.1 Pauli_Y-GATE 2.9.3.2 Pauli_Z-GATE 2.9.3.3 Pauli_S-Gate 2.9.4 Two-Qubit GATE 2.9.5 Controlled NOT(C-NOT) 2.9.6 The Two-Qubits are Swapped Using SWAP_GATE 2.9.7 C-Z-GATE (Controlled Z-GATE) 2.9.8 C-P-GATE (Controlled-Phase-GATE) 2.9.9 Three-Qubit Quantum GATE 2.9.9.1 GATE: Toffoli Gate 2.9.10 F-C-S GATE (Fredkin Controlled Swap-GATE) 2.10 Quantum Computation and Classical Computation Comparison 2.11 Quantum Cryptography 2.12 Quantum Key Distribution – QKD 2.13 Conclusion References Chapter 3 Analysis of Design Quantum Multiplexer Using CSWAP and Controlled-R Gates 3.1 Introduction 3.2 Mathematical Background of Quantum Circuits 3.2.1 Hadamard Gate 3.2.2 CSWAP Gates 3.2.3 Controlled-R Gates 3.3 Methodology of Designing Quantum Multiplexer (QMUX) 3.3.1 QMUX Using CSWAP Gates 3.3.1.1 Generalization 3.3.2 QMUX Using Controlled-R Gates 3.4 Analysis and Synthesis of Proposed Methodology 3.5 Complexity and Cost of Quantum Circuits 3.6 Conclusion References Chapter 4 Artificial Intelligence and Machine Learning Algorithms in Quantum Computing Domain 4.1 Introduction 4.1.1 Quantum Computing Convolutional Neural Network 4.2 Literature Survey 4.3 Quantum Algorithms Characteristics Used in Machine Learning Problems 4.3.1 Minimizing Quantum Algorithm 4.3.2 K-NN Algorithm 4.3.3 K-Means Algorithm 4.4 Tree Tensor Networking 4.5 TNN Implementation on IBM Quantum Processor 4.6 Neurotomography 4.7 Conclusion and Future Scope References Chapter 5 Building a Virtual Reality-Based Framework for the Education of Autistic Kids 5.1 Introduction 5.2 Literature Review 5.3 Proposed Work 5.3.1 Methodology 5.3.2 Work Flow of Neural Style Transfer 5.3.3 A-Frame 5.3.3.1 Setting Up the Virtual World and Adding Components 5.3.3.2 Adding Interactivity Through Raycasting 5.3.3.3 Animating the Components 5.3.4 Neural Style Transfer 5.3.4.1 Choosing the Content and Styling Image 5.3.4.2 Image Preprocessing and Generation of a Random Image 5.3.4.3 Model Design and Extraction of Content and Style 5.3.4.4 Loss Calculation 5.3.4.5 Model Optimization 5.4 Evaluation Metrics 5.5 Results 5.5.1 A-Frame 5.5.2 Neural Style Transfer 5.6 Conclusion References Chapter 6 Detection of Phishing URLs Using Machine Learning and Deep Learning Models Implementing a URL Feature Extractor 6.1 Introduction 6.2 Related Work 6.3 Proposed Model 6.3.1 URL Feature Extractor 6.3.2 Dataset 6.3.3 Methodologies 6.3.3.1 AdaBoost Classifier 6.3.3.2 Gradient Boosting Classifier 6.3.3.3 K-Nearest Neighbors 6.3.3.4 Logistic Regression 6.3.3.5 Artificial Neural Networks 6.3.3.6 Support Vector Machines (SVM) 6.3.3.7 Naïve Bayes Classifier 6.4 Results 6.5 Conclusions References Chapter 7 Detection of Malicious Emails and URLs Using Text Mining 7.1 Introduction 7.2 Related Works 7.3 Dataset Description 7.4 Proposed Architecture 7.5 Methodology 7.5.1 Methodology for the URL Dataset 7.5.2 Methodology for the Email Dataset 7.5.2.1 Overcoming the Overfitting Problem 7.5.2.2 Tokenization 7.5.2.3 Applying Machine Learning Algorithms 7.5.3 Detecting Presence of Malicious URLs in Otherwise Non-Malicious Emails 7.5.3.1 Preparation of Dataset 7.5.3.2 Creation of Features 7.5.3.3 Applying Machine Learning Algorithms 7.6 Results 7.6.1 URL Dataset 7.6.2 Email Dataset 7.6.3 Final Dataset 7.7 Conclusion References Chapter 8 Quantum Data Traffic Analysis for Intrusion Detection System 8.1 Introduction 8.2 Literature Overview 8.3 Methodology 8.3.1 Autoviz 8.3.2 Dataset 8.3.3 Proposed Models 8.3.3.1 Decision Tree 8.3.3.2 Random Forest Classifier Algorithm 8.3.3.3 AdaBoost Classifier 8.3.3.4 Ridge Classifier 8.3.3.5 Logistic Regression 8.3.3.6 SVM-Linear Kernel 8.3.3.7 Naive Bayes 8.3.3.8 Quadratic Discriminant Analysis 8.4 Results 8.5 Conclusion References Chapter 9 Quantum Computing in Netnomy: A Networking Paradigm in e-Pharmaceutical Setting 9.1 Introduction 9.2 Discussion 9.2.1 Exploring Market Functioning via Quantum Network Economy 9.2.1.1 Internal Networking Marketing 9.2.1.2 Layered Marketing 9.2.1.3 Role of Marketing in Pharma Network Organizations 9.2.1.4 Role of Marketing in Vertical Networking Organizations 9.2.1.5 Generic e-Commerce Entity Model in Pharmaceutical Industry 9.2.2 Analyzing the Usability of Quantum Netnomics in Attending Economic Development 9.2.2.1 Theory of 4Ps in Pharma Marketing Mix 9.2.2.2 Buying Behavior of the e-Consumers 9.2.2.3 Maintaining of Privacy and Security via Quantum Technology in e-Structure 9.2.2.4 Interface Influencing Sales 9.3 Results 9.4 Conclusion References Chapter 10 Machine Learning Approach in the Indian Service Industry: A Case Study on Indian Banks 10.1 Introduction 10.2 Literature Survey 10.3 Experimental Results 10.4 Conclusion References Chapter 11 Accelerating Drug Discovery with Quantum Computing 11.1 Introduction 11.2 Working Nature of Quantum Computers 11.3 Use Cases of Quantum Computing in Drug Discovery 11.4 Target Drug Identification and Validation 11.5 Drug Discovery Using Quantum Computers is Expected to Start by 2030 11.6 Conclusion References Chapter 12 Problems and Demanding Situations in Traditional Cryptography: An Insistence for Quantum Computing to Secure Private Information 12.1 Introduction to Cryptography 12.1.1 Confidentiality 12.1.2 Authentication 12.1.3 Integrity 12.1.4 Non-Repudiation 12.2 Different Types of Cryptography 12.2.1 One-Way Processing 12.2.1.1 Hash Function (One-Way Processing) 12.2.2 Two-Way Processing 12.2.2.1 Symmetric Cryptography 12.2.2.2 Asymmetric Cryptography 12.2.3 Algorithms Types 12.2.3.1 Stream Cipher 12.2.3.2 Block Cipher 12.2.4 Modes of Algorithm 12.2.4.1 Cipher Feedback Mode 12.2.4.2 Output Feedback Mode 12.2.4.3 Cipher Block Chaining Mode 12.2.4.4 Electronic Code Book 12.3 Common Attacks 12.3.1 Passive Attacks 12.3.1.1 Traffic Analysis 12.3.1.2 Eavesdropping 12.3.1.3 Foot Printing 12.3.1.4 War Driving 12.3.1.5 Spying 12.3.2 Active Attacks 12.3.2.1 Denial of Service 12.3.2.2 Distributed Denial of Service (DDOS) 12.3.2.3 Message Modification 12.3.2.4 Masquerade 12.3.2.5 Trojans 12.3.2.6 Replay Attacks 12.3.3 Programming Weapons for the Attackers 12.3.3.1 Dormant Phase 12.3.3.2 Propagation Phase 12.3.3.3 Triggering Phase 12.3.3.4 Execution Phase 12.4 Recent Cyber Attacks 12.5 Drawbacks of Traditional Cryptography 12.5.1 Cost and Time Delay 12.5.2 Disclosure of Mathematical Computation 12.5.3 Unsalted Hashing 12.5.4 Attacks 12.6 Need of Quantum Cryptography 12.6.1 Quantum Mechanics 12.7 Evolution of Quantum Cryptography 12.8 Conclusion and Future Work References Chapter 13 Identification of Bacterial Diseases in Plants Using Re-Trained Transfer Learning in Quantum Computing Environment 13.1 Introduction 13.2 Literature Review 13.3 Proposed Methodology 13.3.1 SVM Classifier 13.3.2 Random Forest to Classify the Rice Leaf 13.3.2.1 Image Pre-Processing 13.3.2.2 Feature Extraction 13.3.2.3 Classification 13.4 Experiment Results Conclusion References Chapter 14 Quantum Cryptography 14.1 Fundamentals of Cryptography 14.2 Principle of Quantum Cryptography 14.2.1 Quantum vs. Conventional Cryptography 14.3 Quantum Key Distribution Protocols 14.3.1 Overview and BB84 Protocol 14.3.2 The B92 Protocol 14.3.3 E91 Protocol 14.3.4 SARG04 Protocol 14.4 Impact of the Sifting and Distillation Steps on the Key Size 14.5 Cryptanalysis 14.6 Quantum Key Distribution in the Real World References Chapter 15 Security Issues in Vehicular Ad Hoc Networks and Quantum Computing 15.1 Introduction 15.2 Overview of VANET Security 15.2.1 Security of VANET 15.2.2 Attacks are Classified 15.3 Architectural and Systematic Security Methods 15.3.1 Solutions for Cryptography 15.3.2 Framework for Trust Groups 15.3.3 User Privacy Security System Based on ID 15.4 Suggestions on Particular Security Challenges 15.4.1 Content Delivery Integrity Metrics 15.4.2 Position Detection 15.4.3 Protective Techniques 15.5 Quantum Computing in Vehicular Networks 15.5.1 Securing Automotive Ecosystems: A Challenge 15.5.2 Generation of Quantum Random Numbers (QRNG) 15.6 Quantum Key Transmission (QKD) 15.7 Quantum Internet – A Future Vision 15.7.1 Quantum Internet Applications 15.7.2 Application Usage-Based Categorization 15.8 Conclusions References Chapter 16 Quantum Cryptography with an Emphasis on the Security Analysis of QKD Protocols 16.1 Introduction 16.2 Basic Terminology and Concepts of Quantum Cryptography 16.2.1 Quantum Cryptography and Quantum Key Distribution 16.2.2 Quantum Computing and Quantum Mechanics 16.2.3 Post-Quantum Cryptography 16.2.4 Quantum Entanglement 16.2.5 Heisenberg’s Uncertainty Principle 16.2.6 Qubits 16.2.7 Polarization 16.2.8 Traditional Cryptography vs. Quantum Cryptography 16.3 Trends in Quantum Cryptography 16.3.1 Global Quantum Key Distribution Links 16.3.2 Research Statistics on Quantum Cryptography 16.4 An Overview of QKD Protocols 16.4.1 Introduction to the Prepare-and-Measure Protocols 16.4.2 The BB84 Protocol 16.4.3 B92 Protocol 16.4.4 Six State Protocol (SSP) 16.4.5 SARG04 Protocol 16.4.6 Introduction to the Entanglement-Based Protocols 16.4.7 The E91 Protocol 16.4.8 The BBM92 Protocol 16.5 Security Concerns in QKD 16.6 Future Research Foresights 16.6.1 Increase in Bit Rate 16.6.2 Longer Distance Coverage 16.6.3 Long Distance Quantum Repeaters 16.6.4 Device Independent Quantum Cryptography 16.6.5 Development of Tools for Simulation and Measurements 16.6.6 Global Quantum Communication Network 16.6.7 Integrated Photonic Spaced QKD 16.6.8 Quantum Teleportation References Chapter 17 Deep Learning-Based Quantum System for Human Activity Recognition 17.1 Introduction 17.2 Related Works 17.3 Proposed Scheme 17.3.1 Datasets Description 17.3.2 Pre-Processing 17.3.3 Feature Extraction 17.3.4 Preliminaries 17.3.4.1 Quantum Computing 17.3.4.2 Convolutional Neural Networks 17.3.5 Proposed ORQC-CNN Model 17.3.5.1 Quantum Convolutional Layer 17.3.5.2 Convolutional Layer 17.3.5.3 Max-Pooling Layer 17.3.5.4 Fully Connected Layer 17.3.6 Parameter Selection Using Artificial Gorilla Troops Optimization Algorithm (AGTO) 17.3.6.1 Exploration Phase 17.3.6.2 Exploitation Phase 17.3.6.3 Follow the Silverback 17.3.6.4 Competition for Adult Females 17.3.7 Computational Difficulty 17.4 Results and Discussion 17.4.1 Performance Measure 17.4.2 Performance Analysis of Dataset 1 17.4.3 Performance Analysis of Dataset 2 17.4.4 Comparison 17.5 Conclusion References Chapter 18 Quantum Intelligent Systems and Deep Learning 18.1 Introduction 18.2 Quantum Support Vector Machine 18.3 Quantum Principal Component Analysis 18.4 Quantum Neural Network 18.5 Variational Quantum Classifier 18.6 Conclusion References Index EULA