The book provides invaluable insights into the transformative role of AI and ML in security, offering essential strategies and real-world applications to effectively navigate the complex landscape of today’s cyber threats.
Protecting and Mitigating Against Cyber Threats delves into the dynamic junction of artificial intelligence (AI) and machine learning (ML) within the domain of security solicitations. Through an exploration of the revolutionary possibilities of AI and ML technologies, this book seeks to disentangle the intricacies of today’s security concerns. There is a fundamental shift in the security soliciting landscape, driven by the extraordinary expansion of data and the constant evolution of cyber threat complexity. This shift calls for a novel strategy, and AI and ML show great promise for strengthening digital defenses. This volume offers a thorough examination, breaking down the concepts and real-world uses of this cutting-edge technology by integrating knowledge from cybersecurity, computer science, and related topics. It bridges the gap between theory and application by looking at real-world case studies and providing useful examples.
Protecting and Mitigating Against Cyber Threats provides a roadmap for navigating the changing threat landscape by explaining the current state of AI and ML in security solicitations and projecting forthcoming developments, bringing readers through the unexplored realms of AI and ML applications in protecting digital ecosystems, as the need for efficient security solutions grows. It is a pertinent addition to the multi-disciplinary discussion influencing cybersecurity and digital resilience in the future.
Readers will find in this book:
- Provides comprehensive coverage on various aspects of security solicitations, ranging from theoretical foundations to practical applications;
- Includes real-world case studies and examples to illustrate how AI and machine learning technologies are currently utilized in security solicitations;
- Explores and discusses emerging trends at the intersection of AI, machine learning, and security solicitations, including topics like threat detection, fraud prevention, risk analysis, and more;
- Highlights the growing importance of AI and machine learning in security contexts and discusses the demand for knowledge in this area.
Audience
Cybersecurity professionals, researchers, academics, industry professionals, technology enthusiasts, policymakers, and strategists interested in the dynamic intersection of artificial intelligence (AI), machine learning (ML), and cybersecurity.
Preface xxi
Part I: Foundations of AI & ML in Security 1
1 Foundations of AI and ML in Security 3
Sunil Kumar Mohapatra, Ankita Biswal, Harapriya Senapati, Adyasha Swain and
Swarupa Pattanaik
2 Application of AI and ML in Threat Detection 29
Oviya Marimuthu, Priyadharshini Ravi and Senthil Janarthanan
3 Artificial Intelligence and Machine Learning Applications in Threat
Detection 41
Indu P.V., Preethi Nanjundan and Lijo Thomas
Part II: AI & ML Applications in Threat Detection 57
4 Comparison Study Between Different Machine Learning (ML) Models Integrated
with a Network Intrusion Detection System (NIDS) 59
Aryan Kapoor, Jayasankar K.S., Pranay Jiljith, Abishi Chowdhury, Shruti
Mishra, Sandeep Kumar Satapathy, Janjhyam Venkata Naga Ramesh and Sachi
Nandan Mohanty
5 Applications of AI, Machine Learning and Deep Learning for Cyber Attack
Detection 79
Chandrakant Mallick, Parimal Kumar Giri, Mamata Garanayak and Sasmita Kumari
Nayak
6 AI-Based Prioritization of Indicators of Intelligence in a Threat
Intelligence Sharing Platform 101
Vijayadharshni, Krishan Shankash, Siddharth Tiwari, Shruti Mishra, Sandeep
Kumar Satapathy, Sung-Bae Cho, Janjhyam Venkata Naga Ramesh and Sachi Nandan
Mohanty
7 Email Spam Classification Using Novel Fusion of Machine Learning and Feed
Forward Neural Network Approaches 119
Keshetti Sreekala, Maganti Venkatesh, M. V. Ramana Murthy, S. Venkata Meena,
Srinivas Rathula and A. Lakshmanarao
8 Intrusion Detection in Wireless Networks Using Novel Classification Models
131
Archith Gandla, Dinesh K., Vasu Gambhirrao, R. M. Krsihna Sureddi,
Ramakrishna Kolikipogu and Ramu Kuchipudi
9 Detection and Proactive Prevention of Website Swindling Using Hybrid
Machine Learning Model 147
G. Nithish Rao, J.M.S. Abhinav and M. Venkata Krishna Reddy
Part III: Advanced Security Solutions & Case Studies 161
10 Securing the Future Networks: Blockchain-Based Threat Detection for
Advanced Cyber Security 163
Adusumalli Balaji, T. Chaitanya, Tirupathi Rao Bammidi, Kanugo Sireesha and
Dulam Devee Siva Prasad
11 Mitigating Pollution Attacks in Network Coding-Enabled Mobile Small Cells
for Enhanced 5G Services in Rural Areas 191
Chanumolu Kiran Kumar and Nandhakumar Ramachandran
13 Enhancing Cyber-Security and Network Security Through Advanced Video Data
Summarization Techniques 233
Aravapalli Rama Satish and Sai Babu Veesam
14 Deepfake Face Detection Using Deep Convolutional Neural Networks: A
Comparative Study 267
Krishna Prasanna Gottumukkala, Sirikonda Manasa, Komal Chakravarthy and
Kolikipogu Ramakrishna
15 Detecting Low-Rate DDoS Attacks for CS 283
P. Venkata Kishore, B. Sivaneasan, Amjan Shaik and Prasun Chakrabarti
16 Image Privacy Using Reversible Data Hiding and Encryption 301
Kiranmaie Puvulla, M. Venu Gopalachari, Sreeja Edla, Siddeshwar Vasam and
Tushar Thakur
17 Object Detection in Aerial Imagery Using Object Centric Masked Image
Modeling (OCMIM) 315
Aarthi Pulivarthi, Jitta Poojitha Reddy, Vanka Eshwar Prabhas, T.
Satyanarayana Murthy, Ramesh Babu and Ramu Kuchipudi
18 Encryption and Decryption of Credit Card Data Using Quantum Cryptography
331
Sumit Ranjan, Armaan Munshi, Devansh Gupta, Sandeep Kumar Satapathy, Shruti
Mishra, Abishi Chowdhury, Sachi Nandan Mohanty and Mannava Yesu Babu
19 Securing Secrets: Exploring Diverse Encryption and Decryption Through
Cryptography with Deep Dive to AES 349
Yarradoddi Sai Sreenath Reddy, Gurram Thanmai, Kammila Charan Sri Sai Varma,
Shruti Mishra, Sandeep Kumar Satapathy, Abishi Chowdhury, Sachi Nandan
Mohanty and Mannava Yesu Babu
20 Secure Pass: Hash-Based Password Generator and Checker with Randomized
Function 365
Aneesh Rathore, Ganesh Choudhary, Mradul Goyal, Shruti Mishra, Sandeep Kumar
Satapathy, Janjhyam Venkata Naga Ramesh and Sachi Nandan Mohanty
21 Beyond Passwords: Face Authentication as a Futuristic Solution for Web
Security 379
Paras Yadav, Manya Bhardwaj, Akshita Bhamidimarri, Shruti Mishra, Sandeep
Kumar Satapathy, Janjhyam Venkata Naga Ramesh and Sachi Nandan Mohanty
22 Cryptographic Key Application for Biometric Implementation in Automobiles
401
Priyansh Chatap, Kavish Paul, Akshat Gupta, Sandeep Kumar Satapathy, Sung-Bae
Cho, Shruti Mishra, Janjhyam Venkata Naga Ramesh and Sachi Nandan Mohanty
23 Password Strength Testing: An Overview and Evaluation 419
Tanmay Agrawal, Kaushal Kanna, Azeem, Abishi Chowdhury, Shruti Mishra,
Sandeep Kumar Satapathy, Janjhyam Venkata Naga Ramesh and Sachi Nandan
Mohanty
24 Digital Forensics Analysis on the Internet of Things and Assessment of
Cyberattacks 431
Saswati Chatterjee, Suneeta Satpathy and Pratik Kumar Swain
25 Closing the Security Gap: Towards Robust and Explainable AI for Diabetic
Retinopathy 445
R. S. M. Lakshmi Patibandla
26 Applications of Leveraging Diverse Machine Learning Models for Heart
Stroke Prediction and its Security Aspects in Healthcare 473
Busa Shannu Sri, Kotha Dinesh Sai and U. M. Gopal Krishna
27 Enhancing Healthcare Security: A Revolutionary Methodology for Deep
Learning-Based Intrusion Detection 483
M. Priyachitra, Prasanjit Singh, D. Senthil and Ellakkiya Sekar
28 AI and ML Application in Cybersecurity Hazard Recognition: Challenges,
Opportunities, and Future Perspectives in Ethiopia, Horn of Africa 501
Shashi Kant and Metasebia Adula
References 528
Index 531
Sachi Nandan Mohanty, PhD is an associate professor at the School of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India, He has published 60 articles in journals of international repute, edited 24 books, and serves as an editor for several international journals. His research interests include data mining, big data analysis, cognitive science, fuzzy decision making, brain-computer interface, cognition, and computational intelligence.
Suneeta Satpathy, PhD is an associate professor in the Center for Artificial Intelligence and Machine Learning at Siksha O. Anusandhan University, India. She has published several papers in international journals and conferences of repute and edited numerous books. Her research interests include computer forensics, cyber security, data fusion, data mining, big data analysis, and decision mining.
Ming Yang, PhD is a professor in the College of Computing and Software Engineering at Kennesaw State University, Georgia, USA and serves as a consultant for many companies. He has published over 70 peer-reviewed conference and journal papers and book chapters in addition to serving as an editor for several journals. His research interests include image processing, multimedia communication, computer vision, and machine learning.
D. Khasim Vali, PhD is an assistant professor in the School of Computer Science and Engineering, the Vellore Institute of Technology, Andhra Pradesh University, India, with over 18 years of teaching experience. He has 21 international publications to his credit and is a life member of ISTE and IETE. His research interests include artificial intelligence, machine learning, and deep learning.
