COVID and Pandemic Issues

AAP Advances in Artificial Intelligence and Robotics

The Fusion of Artificial Intelligence and Soft Computing Techniques for Cybersecurity
Editors: M. A. Jabbar, PhD
Sanju Tiwari, PhD
Subhendu Kumar Pani, PhD
Stephen Huang, PhD

The Fusion of Artificial Intelligence and Soft Computing Techniques for Cybersecurity

Now on Press
Pub Date: June 2024
Hardback Price: $169.95 US | £131.00
Hard ISBN: 9781774914809
E-Book ISBN: 9781003428503
Pages: 294pp w/index
Binding Type: Hardback/ eBook
Series: AAP Advances in Artificial Intelligence and Robotics
Notes: 67 b/w illustrations

With the ever-increasing threat of cyber-attacks, especially as the COVID-19 pandemic helped to ramp up the use of digital communications technology, there is a continued need to find new ways to maintain and improve cybersecurity. This new volume investigates the advances in artificial intelligence and soft computing techniques in cybersecurity. It specifically looks at cybersecurity during the COVID-19 pandemic, the use of cybersecurity for cloud intelligent systems, applications of cybersecurity techniques for web applications, and cybersecurity for cyber-physical systems. A diverse array of technologies and techniques are explored for cybersecurity applications, such as the Internet of Things, edge computing, cloud computing, artificial intelligence, soft computing, machine learning, cross-site scripting in web-based services, neural gas (GNG) clustering technique, and more.

The volume gives special attention to the impact of the cyber-attack surge during COVID on healthcare and business organizations and the emerging cybersecurity technologies aimed to provide better cybersecurity, including security challenges in mobile app development.

The book also looks at cloud and edge computing security using artificial intelligence and soft computing techniques. Various integration technologies with regards to cyber-physical systems are also described as well as applications of cybersecurity using machine learning approaches. Other chapters look at an efficient vehicle tracking system to enhance security, network forensic attacks using an enhanced growing neural gas (GNG) clustering technique, and more. An audit chapter aggregates data from other sources papers regarding IoT, AI, and cyber-assaults.

The Fusion of Artificial Intelligence and Soft Computing Techniques for Cybersecurity is written for a broad audience of those interested in the applications of artificial intelligence in cybersecurity, including professionals, policymakers, business leaders, network administrators, and many others.

CONTENTS:
Preface

PART I: CYBERSECURITY DURING COVID-19 PANDEMIC
1. An Insight into Cybersecurity During the Covid-19 Pandemic
Rayeesa Tasneem and M. A. Jabbar

2. Cyber-Attack Surge in a Covid Scenario: Reasons and Consequences
Neeranjan Chitare, Maitreyee Ghosh, Shankru Guggari, and M. A. Jabbar

3. IoT in Security: Impact and Challenges During a Pandemic
Sonia Sharma

4. Mobile App Development Privacy and Security Checklist During Covid-19
Hena Iqbal, Tanjinsikder, Yasmin Alhayek, Noora Alfurais, and Nujuom Assar

PART II: CYBERSECURITY FOR CLOUD INTELLIGENT SYSTEMS
5. Cloud and Edge Computing Security Using Artificial Intelligence and Soft Computing Techniques
N. S. Gowri Ganesh, R. Roopa Chandrika, and A. Mummoorthy

6. Security in IoT Using Artificial Intelligence
Sanchari Saha

7. Cybersecurity for Intelligent Systems
Abinaya Inbamani, N. Divya, R. R. Rubia Gandhi, M. Karthik, and M. Sivaram Kumar

PART III: APPLICATIONS OF CYBERSECURITY TECHNIQUES FOR WEB APPLICATIONS
8. Analysis of Advanced Manual Detection and Robust Prevention of Cross-Site Scripting in Web-Based Services
Smit Sawant, Gaurav Choudhary, Shishir Kumar Shandilya, Lokesh Giripunje, And Vikas Sihag

9. Soft Computing Techniques for Cyber-Physical Systems
R. R. Rubia Gandhi, Abinaya Inbamani, N. Divya, M. Karthik, and E. Ramya

10. Cybersecurity Using Machine Learning Approaches: A Systematic Review
Mohankumar K. N. and Pavankumar E.

PART IV: CYBERSECURITY FOR CYBER-PHYSICAL SYSTEMS
11. Efficient Vehicle Tracking System in Dense Traffic to Enhance Security
Bharathi S., Amisha R. Naik, and Piyush Kumar Pareek

12. Optimized Analysis of Network Forensic Attacks Using Enhanced Growing Neural Gas (GNG) Clustering Technique
A. Dhanu Saswanth, V. Kavitha, B. Sundaravadivazhagan, and R. Karthikeyan

13. Security in IoT: Systematic Review
K. Tejasvi, Ruqqaiya Begum, and M. A. Jabbar

Index


About the Authors / Editors:
Editors: M. A. Jabbar, PhD
Professor and Head, Department CSE(AI&ML), Vardhaman College of Engineering, Hyderabad, Telangana, India

M. A. Jabbar, PhD, is a Professor and Head of the Department CSE (AI & ML), Vardhaman College of Engineering, Hyderabad, Telangana, India. He obtained a Doctor of Philosophy (PhD) in 2015 from Jawaharlal Nehru Technological University, Hyderabad and Telangana, India. He has been teaching for more than 20 years. His research interests include artificial intelligence, big data analytics, bioinformatics, cybersecurity, machine learning, attack graphs, and intrusion detection systems. He has published over 60 papers in various journals and conferences and served as a technical committee member for more than 70 international conferences. He has also been editor for several conferences (1st ICMLSC 2018, SOCPAR 2019, and ICMLSC 2020) and has been involved in organizing international conference as an organizing chair, program committee chair, publication chair, and reviewer (SoCPaR, HIS, ISDA, IAS, WICT, NABIC, etc.). He is co-editor of the books The Fusion of Internet of Things, AI, and Cloud Computing in Health Care: Opportunities and Challenges (Springer); Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities (CRC Press); Emerging Technologies and Applications for a Smart and Sustainable World (Bentham Science); and Machine Learning Methods for Signal, Image and Speech Processing (River Publisher).

Sanju Tiwari, PhD
Senior Researcher, Universidad Autonoma de Tamaulipas, Mexico

Sanju Tiwari, PhD, is a Senior Researcher at the Universidad Autonoma de Tamaulipas, Mexico. She has worked as a postdoctoral researcher in the Ontology Engineering Group at the Universidad Polytecnica De Madrid, Spain. Prior to this, she has worked as a research associate for a sponsored research project, “Intelligent Real time Situation Awareness and Decision Support System for Indian Defence,” funded by the Defence Research and Development Organisation (DRDO), New Delhi, in the Department of Computer Applications, National Institute of Technology, Kurukshetra, India. In this project, she developed and evaluated a decision support system for Indian Defence. Her current research interests include ontology engineering, knowledge graphs, linked data generation and publication, semantic web, reasoning with SPARQL, and machine intelligence.

Subhendu Kumar Pani, PhD
Professor, Department of Computer Science and Engineering; Research Coordinator, Krupajal Engineering College (KEC) Bhubaneswar, India

Subhendu Kumar Pani, PhD, is Professor in the Department of Computer Science and Engineering and Research Coordinator, Krupajal Engineering College (KEC) Bhubaneswar, India. He was formerly Professor in the Department of Computer Science and Engineering and Research Coordinator at Orissa Engineering College (OEC), Bhubaneswar, India. He has more than 15 years of teaching and research experience. His research interests include data mining, big data analysis, web data analytics, fuzzy decision-making, and computational intelligence. He is the recipient of five researcher awards. In addition to research, he has guided two PhD students and 31 MTech students. He has published over 50 international journal papers (25 Scopus indexed). His professional activities include roles as associate editor, editorial board member, and/or reviewer of various international journals. He is associated with a number of conferences and societies. He has more than 100 international publications, five authored books, two edited books, and ten book chapters to his credit. He is a fellow of the Scientific Society of Advance Research and Social Change and a life member in many other professional organizations.

Stephen Huang, PhD
Professor of Computer Science, University of Houston, Texas

Stephen Huang, PhD, Professor of Computer Science at the University of Houston (UH), Texas, USA, has more than 40 years of experience in computer science teaching, research, and administration. He also serves as the Director of Research at the Center for Information Security Research and Education at UH. His research interests include cybersecurity, intrusion detection, and algorithms. He has published many journals and conference papers and has supervised and graduated over 30 MS and ten PhD students. Dr. Huang has served in several administrative positions at UH, including Director of Graduate Studies, Associate Chairman, and Department Chairman. Dr. Huang received his PhD degree in Computer Science from the University of Texas-Austin in 1981. He was a National Research Council–NASA Senior Research Associate at the NASA Goddard Space Flight Center, Greenbelt, Maryland, during 1989-90.




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