Electronics and Communications Technology

Mastering Malware Development and Analysis
A Comprehensive Guide to Hybrid Malware Analysis and Virtual Sandboxing

Editors: Bishwajeet Kumar Pandey, PhD
Deepak Bhaskar Acharya, PhD
Divya B., PhD (NITK)

Mastering Malware Development and Analysis

In Production
Pub Date: Forthcoming December 2026
Hardback Price: $190 USD | £150 UK
Hard ISBN: 9781779646224
E-Book ISBN: 978-1-77964-623-1
Pages: Est. 296 pp w index
Binding Type: Hardback / ebook
Notes: 40 b/w illustrations

In an era where cyber threats are growing in complexity, the need for advanced malware analysis techniques has become more critical than ever. Malware continues to evolve with the help of polymorphism, obfuscation, and sophisticated delivery mechanisms, which challenge traditional security measures and demand a novel approach to analysis.

This new book, Mastering Malware Developments and Analysis: A Comprehensive Guide to Hybrid Malware Analysis and Virtual Sandboxing, addresses the need for advanced solutions to the growing and ever-evolving cyber threats.

Spanning multiple dimensions of malware research, this volume combines static and dynamic analysis techniques, artificial intelligence integration, reverse engineering, and the deployment of sandbox environments to simulate and study malware behavior. The hybrid analysis approach highlighted in this book acknowledges that no single method is sufficient on its own: real defense requires layered, intelligent responses that adapt as threats do.

Each chapter provides an in-depth exploration of a specific topic, contributed by experts from academia and industry. From the fundamentals of virtual sandboxing to cutting-edge innovations in behavior-driven detection, the book provides actionable insights and practical tools for both foundational learning and advanced research.

Serving as a comprehensive guide that not only addresses current challenges but also anticipates future trends in malware development and countermeasures, this volume will be valuable for students in cybersecurity courses, professionals in threat analysis roles, and researchers seeking to advance the science of malware detection.

CONTENTS:
Preface

1. Exploring Emerging Techniques and Tools for Malware Analysis
Ankit Jain, Anita Shukla, Vivek Kumar, Imran Ullah Khan, Keshav Kumar, and Kamini Simi Bajaj

2. Advanced Malware Analysis Techniques: Unpacking, Debugging, and Reverse Engineering
Mayur R. Bhoyar

3. Behavioral Analysis of Sandboxing: Techniques, Challenges, and Applications
Mohit Kumar Srivastava, Keshav Kumar, Preeti Agarwal Mittal, Pradeep Kumar Gupta, and Sumiti Narayan Tewari

4. The Role of REMnux for Malware Analysis
Kumar Ayush, Medha Sree Anand, Tanvir H. Sardar, Laura Aldasheva, Saurav Mallik, and Mahendra Kumar Gourisaria

5. The Role of FlareVM for Malware Analysis
Medha Sree Anand, Kumar Ayush, Tanvir H. Sardar, Laura Aldasheva, Saurav Mallik, and Mahendra Kumar Gourisaria

6. Dynamic Analysis of Wannacry Ransomware
Abdullah Al Siam, Sadequzzaman Shohan, and Nuruzzaman Faruqui

7. Machine Learning in Malware Analysis
Samuel Matia Kangoni

8. Future of Malware Analysis
Emre Tokgoz

9. Configuring an AWS Cloud Sandbox Environment for Testing
Swati Singh, Amanpreet Kaur, and Yonis Gulzar

10. Malware Obfuscation and Evasion Techniques
Attiuttama, Sanjay Kumar Sharma, and Satya Prakash Yadav

11. Building a Local Virtual Sandbox: Windows 11, Kali Linux, and REMnux on VirtualBox
Anurag Reddy Ekkati

12. Creating a Cloud Sandbox on AWS
Muhammad Atif Saeed

13. Design and Development of Malware Using MSFVenom, NJRat, and Other Malware Development Environments
Muhammad Atif Saeed

Index


About the Authors / Editors:
Editors: Bishwajeet Kumar Pandey, PhD
Professor, GL Bajaj Institute of Technology and Management, Greater Noida, India

Bishwajeet Pandey, PhD, is a Professor at the GL Bajaj Institute of Technology and Management, Greater Noida, India. He has been a senior member of IEEE since 2019. He has taught and held leadership roles at various esteemed institutions such as Chitkara University, Chandigarh; Jain University, Bangalore; Astana IT University, Kazakhstan; Eurasian National University, Kazakhstan; Walsh College, Michigan, USA; and UCSI University, Malaysia. Dr. Pandey is a prolific researcher with over 30 published books and more than 220 research papers indexed in Scopus. He has visited 49 countries, participated in over 100 international conferences, and co-authored papers over 200 professors from nearly 100 universities across 42 nations. His work has garnered over 4200+ citations. In 2023, Dr. Pandey was honored with the prestigious Professor of the Year Award at Lords Cricket Ground by the London Organisation of Skills Development.

Deepak Bhaskar Acharya, PhD
Principal Research Scientist, Information Technology and Systems Center, University of Alabama, Huntsville, USA

Deepak Bhaskar Acharya, PhD, is a scholar and a teacher with distinguished research experience in the field of machine learning, deep learning, and computer science applications. A senior member of IEEE, he is a Principal Research Scientist with the Information Technology and Systems Center, University of Alabama, Huntsville, USA. He has applied advanced machine learning techniques, especially in NASA-funded projects, to develop super-resolution tools for precipitation data and Earth observation systems to address public health issues in Sub-Saharan Africa. He mentors graduate and undergraduate students and serves on academic review boards for several top-notch journals, helping to further the field of AI and computer science. His areas of research interests include machine learning and deep learning, including graph neural networks, clustering techniques, and Gumbel-Softmax distribution. He received his Master of Science degree in computer science and PhD degree from The University of Alabama in Huntsville (UAH).

Divya B., PhD (NITK)
Assistant Professor, Department of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal, India

Divya B., PhD (NITK), holds the position of Assistant Professor with the Department of Electronics and Communication Engineering at the Manipal Institute of Technology, Manipal, India. Her teaching career spans over 14 years. Her expertise includes applied technology subparts, such as machine learning, deep learning, and signal processing, to which she also actively contributes research and development. She has taken part in a number of projects that implement ML and DL technologies for enhancing image analysis, data analysis, and prediction. Her research interests include machine learning and efforts related to signal processing and biomedical image processing. She received a Bachelor of Engineering degree in electronics and communication engineering from Visvesvaraya Technological University, Belagavi, and the Master of Technology degree in signal processing from the Siddaganga Institute of Technology, Tumakuru, India. She has submitted her PhD thesis at the National Institute of Technology Karnataka, Surathkal, India.




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