Evolution and Applications of Quantum Computing E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 451

Veröffentlichungsjahr: 2023

Beschreibung

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.

Leseprobe

Table of Contents

Cover

Series Page

Title Page

Copyright Page

Preface

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

1.7 Quantum Computation

1.8 Comparison of Quantum and Classical Computation

1.9 Quantum Cryptography

1.10 QKD

1.11 Conclusion

References

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

2.10 Quantum Computation and Classical Computation Comparison

2.11 Quantum Cryptography

2.12 Quantum Key Distribution – QKD

2.13 Conclusion

References

3 Analysis of Design Quantum Multiplexer Using CSWAP and Controlled-R Gates

3.1 Introduction

3.2 Mathematical Background of Quantum Circuits

3.3 Methodology of Designing Quantum Multiplexer (QMUX)

3.4 Analysis and Synthesis of Proposed Methodology

3.5 Complexity and Cost of Quantum Circuits

3.6 Conclusion

References

4 Artificial Intelligence and Machine Learning Algorithms in Quantum Computing Domain

4.1 Introduction

4.2 Literature Survey

4.3 Quantum Algorithms Characteristics Used in Machine Learning Problems

4.4 Tree Tensor Networking

4.5 TNN Implementation on IBM Quantum Processor

4.6 Neurotomography

4.7 Conclusion and Future Scope

References

5 Building a Virtual Reality-Based Framework for the Education of Autistic Kids

5.1 Introduction

5.2 Literature Review

5.3 Proposed Work

5.4 Evaluation Metrics

5.5 Results

5.6 Conclusion

References

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

6.4 Results

6.5 Conclusions

References

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

7.6 Results

7.7 Conclusion

References

8 Quantum Data Traffic Analysis for Intrusion Detection System

8.1 Introduction

8.2 Literature Overview

8.3 Methodology

8.4 Results

8.5 Conclusion

References

9 Quantum Computing in Netnomy: A Networking Paradigm in e-Pharmaceutical Setting

9.1 Introduction

9.2 Discussion

9.3 Results

9.4 Conclusion

References

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

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

12 Problems and Demanding Situations in Traditional Cryptography: An Insistence for Quantum Computing to Secure Private Information

12.1 Introduction to Cryptography

12.2 Different Types of Cryptography

12.3 Common Attacks

12.4 Recent Cyber Attacks

12.5 Drawbacks of Traditional Cryptography

12.6 Need of Quantum Cryptography

12.7 Evolution of Quantum Cryptography

12.8 Conclusion and Future Work

References

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

13.4 Experiment Results

Conclusion

References

14 Quantum Cryptography

14.1 Fundamentals of Cryptography

14.2 Principle of Quantum Cryptography

14.3 Quantum Key Distribution Protocols

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

15 Security Issues in Vehicular Ad Hoc Networks and Quantum Computing

15.1 Introduction

15.2 Overview of VANET Security

15.3 Architectural and Systematic Security Methods

15.4 Suggestions on Particular Security Challenges

15.5 Quantum Computing in Vehicular Networks

15.6 Quantum Key Transmission (QKD)

15.7 Quantum Internet – A Future Vision

15.8 Conclusions

References

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

16.3 Trends in Quantum Cryptography

16.4 An Overview of QKD Protocols

16.5 Security Concerns in QKD

16.6 Future Research Foresights

References

17 Deep Learning-Based Quantum System for Human Activity Recognition

17.1 Introduction

17.2 Related Works

17.3 Proposed Scheme

17.4 Results and Discussion

17.5 Conclusion

References

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

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1

Rectilinear, diagonal basis.

Figure 1.2

Photon polarizations.

Figure 1.3

Representation of photon polarization.

Figure 1.4

Representation of photon polarization.

Figure 1.5

Photon polarization in diagonal basis (of binary 0).

Figure 1.6

Representation of photon polarization.

Figure 1.7

Toffoli gate.

Chapter 2

Figure 2.1

Quadratic and corner basis.

Figure 2.2

Photon polarization.

Figure 2.3

Photon polarizations using quadratic basis.

Figure 2.4

Photon polarization in quadrilateral basis.

Figure 2.5

Photon polarization in diagonal basis (of binary 0).

Figure 2.6

Photon polarization in diagonal basis (of binary 1).

Figure 2.7

Three-Qubit quantum gate.

Figure 2.8

Insecure quantum channel communication.

Figure 2.9

Secure quantum channel communication.

Chapter 3

Figure 3.1

A multiplexer and demultiplexer.

Figure 3.2

Circuit representation and matrix of a CSWAP gate.

Figure 3.3

Circuit and matrix representaion of controlled-R gate.

Figure 3.4

Circuit representation of a 4:1 QMUX.

Figure 3.5

Circuit representation of a 8:1 Mux using CSWAP gates.

Figure 3.6

Circuit to encode qubits to be multiplexed in

q

1

.

Figure 3.7

Inversion circuit to get output state of

q

1

same as the selected qubit.

Figure 3.8

QMUX with classical register as select pin.

Figure 3.9

An information decoder circuit at the receiver end that violates Holevo's Theorem.

Chapter 4

Figure 4.1

The figure shows how conventional computing technology evolves into quantum computing technology...

Figure 4.2

The increase in papers published on quantum machine intelligence since 2012 is shown in the graph.

Figure 4.3

Example for machine learning prediction.

Figure 4.4

The quantum minimization algorithm’s quantum circuit.

Figure 4.5

Datasets for training and testing the quantum KNN algorithm (four classes).

Figure 4.6

For various SWAP-test and QMA iterations, confusion matrices are generated.

Figure 4.7

Complexity of the KNN algorithm’s calculations. As in the previous example, left k < d and right k > d only when d exceeds...

Figure 4.8

Four classes in an unlabeled dataset.

Figure 4.9

The K-means algorithm’s computational complexity.

Figure 4.10

TTN quantum circuit architecture.

Figure 4.11

Comparison of Neurotomography with MLE tomography. There was a total of 2,000 trials conducted...

Chapter 5

Figure 5.1

Autism statistics.

Figure 5.2

Flow of work.

Figure 5.3

A-Frame components.

Figure 5.4

A-Frame components from other angle.

Figure 5.5

Content image.

Figure 5.6

Style image.

Figure 5.7

Architecture of VGG-19.

Figure 5.8

Backpropagation.

Figure 5.9

Backpropagation algorithm working.

Figure 5.10

Content loss.

Figure 5.11

Output image.

Figure 5.12

Transmitter section.

Figure 5.13

Receiver section.

Figure 5.14

A star network topology.

Graph 5.1

Age wise participation in VR program.

Graph 5.2

Characteristics of autistic kids surveyed.

Chapter 6

Figure 6.1

Proposed methodology.

Figure 6.2

URL substrings visualization.

Figure 6.3

Flowchart of the extraction process.

Figure 6.4

Boxplot visualizations for lexical features.

Figure 6.5

Visualization for the count of URLs.

Figure 6.6

Proposed artificial neural network model.

Chapter 7

Figure 7.1

Balanced URL dataset.

Figure 7.2

Final columns of URL dataset.

Figure 7.3

Information gain.

Figure 7.4

Balanced email dataset.

Figure 7.5

Final columns of dataset.

Chapter 8

Figure 8.1

Proposed methodology.

Figure 8.2

Flowchart for AutoViz.

Figure 8.3

Histogram distribution of predicted as against “Label”.

Figure 8.4

Percentage and frequency distribution of “Label”.

Figure 8.5

Pivot table by forward packet length and forward header length for “Label”.

Figure 8.6

Histogram distribution of Label as against “Predicted”.

Figure 8.7

Percentage and frequency distribution of “Predicted”.

Figure 8.8

Box plot of Packet length max for each “Predicted”.

Figure 8.9

Visualization for the count of attacks in 1

st

dataset.

Figure 8.10

Visualization for the count of attacks in 2

nd

dataset.

Figure 8.11

Visualization for the count of attacks in 3

rd

dataset.

Figure 8.12

Assessing algorithm performances on 1

st

created dataset.

Figure 8.13

Assessing algorithm performances on 2

nd

created dataset.

Figure 8.14

Assessing algorithm performances on 3

rd

created dataset.

Chapter 9

Figure 9.1

Challenges in accessing medicines from retail pharmaceutical stores.

Figure 9.2

Layered networking in management.

Figure 9.3

Role of marketing in internal networking firms.

Figure 9.4

Role of marketing in vertical synergy.

Figure 9.5

e-commerce entity model.

Chapter 10

Figure 10.1

Classifiers.

Figure 10.2

Comparing various classifiers.

Figure 10.3

Evaluating the performance.

Chapter 11

Figure 11.1

Schematic diagrams of two quantum computing paradigms...

Chapter 12

Figure 12.1

Symmetric key encryption.

Figure 12.2

Various symmetric key algorithms.

Figure 12.3

Asymmetric key cryptography.

Figure 12.4

Various asymmetric key algorithms.

Figure 12.5

ASCII characters after applying key.

Figure 12.6

Modes of algorithm.

Figure 12.7

Various types of passive attacks.

Figure 12.8

Traffic analysis.

Figure 12.9

Eavesdropping.

Figure 12.10

War driving.

Figure 12.11

Various types of active attacks.

Figure 12.12

Distributed denial.

Figure 12.13

Distributed denial of service.

Figure 12.14

Masquerade.

Figure 12.15

Trojan attack.

Figure 12.16

Different phases of the virus...

Chapter 13

Figure 13.1

Common diseases and healthy plant images from dataset.

Figure 13.2

Sample images of different class labels in ImageNet dataset.

Figure 13.3

“AlexNet” pre-trained model architecture.

Figure 13.4

Input of scanned image and output of the mask image using HOG.

Figure 13.5

Classification of image masked in...

Figure 13.6

Original image transformed to resize image.

Figure 13.7

Numerical representation of feature extraction.

Figure 13.8

Classification using random forest algorithm.

Figure 13.9

Proposed architecture for classing using AlexNet.

Figure 13.10

(a) First section of summary model. (b) Second section of summary model.

Figure 13.11

A sample screenshot of Epochs using the proposed model.

Figure 13.12

Evaluation graphs for analysis.

Figure 13.13

Training and test graphs.

Chapter 14

Figure 14.1

Symmetric encryption.

Figure 14.2

Asymmetric encryption.

Figure 14.3

Quantum cryptography...

Figure 14.4

Illustration of convention cryptography and quantum cryptography...

Figure 14.5

The BB84 protocol by Bennet and Brassard...

Figure 14.6

E91 protocol representation.

Figure 14.7

Polarization filters.

Figure 14.8

Polarization filters.

Figure 14.9

Impact of sifting and distillation steps on key size.

Figure 14.10

The process of BB84 key distribution...

Figure 14.11

Bloch sphere...

Chapter 15

Figure 15.1

VANET attacks classification and examples.

Figure 15.2

Architecture for the trust grouping framework and TPM.

Figure 15.3

Flowchart for the defensive mechanism stage.

Figure 15.4

Security for automotive ecosystems.

Figure 15.5

Quantum internet applications.

Figure 15.6

Stages of a quantum network.

Figure 15.7

Phases of the quantum internet’s development.

Chapter 16

Figure 16.1

Quantum bits.

Figure 16.2

Working of BB84 Protocol.

Figure 16.3

BB84 – Eavesdropping.

Figure 16.4

Sending 8 bits of a secret key in BB84.

Figure 16.5

The three conjugate bases of SSP.

Figure 16.6

Sifting in SARG04.

Figure 16.7

Ekert’s protocol.

Figure 16.8

Working of E91 protocol.

Figure 16.9

BBM92 protocol.

Chapter 17

Figure 17.1

Working flow of proposed ideal.

Figure 17.2

Activities from UT- Dataset 1: shaking hands, pointing, punching, hugging, kicking, and assertive.

Figure 17.3

Sample images of olympic dataset.

Figure 17.4

Block diagram for proposed ORQC-CNN model.

Figure 17.5

Graphical description for dataset 1.

Figure 17.6

Graphical description for dataset 2.

Figure 17.7

Comparison of proposed AGTO with different classifiers.

List of Tables

Chapter 3

Table 3.1

Truth table of CSWAP gate.

Chapter 4

Table 4.1

IBM TTN implementation.

Chapter 5

Table 5.1

A-Frame entity description.

Table 5.2

Description of NST loss functions.

Table 5.3

Performance metrics of A-Frame.

Table 5.4

Result of NST.

Chapter 6

Table 6.1

Features based on the whole URL.

Table 6.2

Features based on domain properties.

Table 6.3

Features based on directory properties.

Table 6.4

File features based on file properties.

Table 6.5

Parameter features based on parameter properties.

Table 6.6

Attributes based on external services.

Table 6.7

Comparative result analysis.

Chapter 7

Table 7.1

Accuracy obtained with information gain feature selection.

Table 7.2

Accuracy obtained for the email dataset.

Table 7.3

Accuracy obtained with final dataset.

Chapter 8

Table 8.1

Algorithms used in AutoML.

Table 8.2

Comparative result analysis.

Chapter 12

Table 12.1

Various hash functions.

Table 12.2

Conversion from plain text to binary.

Table 12.3

Ex-or truth table for reference.

Table 12.4

Various types of attacks and its damage level.

Chapter 13

Table 13.1

Common pathological diseases in plants.

Table 13.2

Illustration of traditional versus intelligent automation.

Table 13.3

Comparative analysis.

Table 13.4

Evaluation metrics analysis.

Chapter 16

Table 16.1

The bit values for polarized photons.

Table 16.2

Comparison of traditional cryptography and quantum cryptography.

Table 16.3

Developments in quantum cryptographic trends.

Table 16.4

Indian research organizations working on quantum cryptography.

Chapter 17

Table 17.1

Layer summary.

Table 17.2

Confusion matrix.

Table 17.3

Comparative analysis of proposed technique.

Table 17.4

Comparative analysis of proposed technique.

Table 17.5

Comparative analysis of proposed AGTO with various classifiers.

Guide

Cover

Table of Contents

Series Page

Title Page

Copyright

Preface

Begin Reading

Index

End User License Agreement

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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106

Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])

Evolution and Applications of Quantum Computing

Edited by

Sachi Nandan Mohanty

School of Computer Science & Engineering, VIT AP University, Amaravati, Andhra Pradesh, India

Rajanikanth Aluvalu

Department of IT, Chaitanya Bharathi Institute of Technology, Hyderabad, India

and

Sarita Mohanty

Department of Computer Science, Odisha University of Agriculture & Technology, Bhubaneswar, India

This edition first published 2023 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2023 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.

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Library of Congress Cataloging-in-Publication Data

ISBN 9781119904861

Cover image: Pixabay.ComCover design by Russell Richardson

Preface

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 begins with the procedure for designing one of the most important combinational circuits, called the quantum multiplexer with secured quantum gate (CSWAP), that aids in implementing quantum entanglement to provide secured communication. Also provided is a description of the pioneering work being done on the interaction between artificial intelligence, machine learning and quantum computing along with their potential role in the world of big data. Next, the book guides you towards detecting malicious emails and URLs by using quantum text mining algorithms and further helps by teaching the algorithm needed to distinguish between phishing and benign sites. Also included is an interesting chapter on application machine learning to detect phishing URLs and the procedure to implement URL feature extractor. Emphasis is placed on the increasing vulnerabilities a system has to cybersecurity attacks in the chapter on quantum data traffic analysis for intrusion detection system. Furthermore, you will find chapters on interdisciplinary fields like quantum computation in Indian banks, netnomy and vehicular ad-hoc networks, virtual reality in education of autistic children, and quantum computing for identifying bacterial diseases and accelerating drug discovery. The book also touches on the critical domain of traditional classical cryptography and quantum cryptography along with their substantial difference and their role in providing a safe and secure communication system.

Almost every application of quantum computing is covered in this book, so by the end of it you will have an encompassing knowledge about this wide field and its potential offshoots in the digitalized era. Moreover, it is an ideal book for newbies in the field of quantum physics, with simple and lucid language for better understanding. All in all, the updated knowledge on the different dynamics of quantum computing covered in this book will leave you amazed.

The Editors

February 2023