Privacy and Security in FinTech, Healthcare, and Social Applications

Inbunden, Engelska, 2026

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Beskrivning

This book provides a timely and comprehensive overview on the cybersecurity challenges in our increasingly connected digital world. With billions of devices projected to be online by 2030, there is urgent need for secure communication, data protection, and privacy across critical sectors. Structured into four key sections—blockchain for healthcare and vehicular systems; secure protocols for medical images; privacy in FinTech; and privacy-preserving federated learning—the book presents state-of-the-art research and practical solutions. Topics include blockchain integration in IoMT and IoV, lightweight cryptographic algorithms, secure image transmission for ASD diagnosis, and DNA-RSA-based encryption for medical data. Further, this book presents innovations like FLEX-HAND for secure vehicle handovers, quantum homomorphic encryption for real-time fraud detection, and AI-driven fraud analytics. Advanced biometric systems using fingerprint and iris data are explored, along with federated learning models that protect user data in healthcare applications like heart disease and diabetic retinopathy detection.Key Features:Provides a detailed review of Secure protocols, algorithms, models, and Security infrastructure for the Internet of Things from past, present, and future.Presents state-of-the-art security enhancements for Fast authentication and privacy preservation schemes for FinTech Industry 4.0.Blockchain integration in IoT, IoV, and IoMT using handover authentication schemes to maintain security and privacy.Explains the practical examples and applications of these algorithms in real-world situations.Focus on emerging domains in IoV, IoT, and IoMT applications for providing information security, authentication schemes to maintain security and privacy.

Produktinformation

Utgivningsdatum:2026-02-25
Mått:156 x 234 x 19 mm
Vikt:670 g
Format:Inbunden
Språk:Engelska
Antal sidor:254
Förlag:Taylor & Francis Ltd
ISBN:9781041045908

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Mer om författaren

Dr. Sriramulu Bojjagani (Senior Member, IEEE) received his joint Ph.D. degree from the School of Computer and Information Sciences, University of Hyderabad, and the Institute for Development and Research in Banking Technology (IDRBT), established by the Reserve Bank of India (RBI). He is currently an Assistant Professor in the Department of Computer Science and Engineering at SRM University-AP, Amaravati, India.He has contributed numerous publications to reputed international journals, including IEEE Transactions, Elsevier, Springer, and Wiley, as well as several book chapters. His research interests include secure protocol design and formal verification for emerging technologies such as the Internet of Vehicles (IoV), Internet of Things (IoT), and Internet of Medical Things (IoMT).He is the inventor of several patents in the areas of cybersecurity, secure communications, and intelligent connected systems. He actively contributes to the research community as a Technical Program Committee (TPC) member for several international conferences. Since 2024, he has been serving on the Editorial Board of Discover Computing (Springer Nature), an SCIE- and Scopus-indexed journal. He also regularly serves as a reviewer for prestigious journals, including IEEE Transactions.In recognition of his research contributions, he received a cash prize at the IDRBT Annual Awards 2019 for his work on “A Secure End-to-End Proximity NFC-Based Mobile Payment Protocol,” published in Computer Standards & Interfaces (Elsevier). He also received the Best Paper Award at the IEEE International Conference on Intelligent Computing and Emerging Communication Technologies (ICEC-2024) held at SRM University-AP, Amaravati.Dr. V. Dinesh Reddy has a PhD from the University of Hyderabad, India, and is a postdoctoral researcher at the University of Stuttgart, Germany. He is an assistant professor at SRM University, AP, India. He has about 12 years of experience in both academic and industrial research, in addition to working in product-oriented companies as an AI consultant for major corporations. He has 3 US and 1 Indian patents and a strong publication record in SCI-indexed journals. He has deep knowledge of machine learning approaches, optimization algorithms, and expertise in cloud computing. Well-versed with development details of cloud and fog simulators- CloudSim, iFogSim, etc. He has been a reviewer for several reputed journals. His research interests lie in Cloud/Edge/Service Oriented Computing and Quantum computing.Dr. Sumalatha Saleti is an Assistant Professor in the Department of Computer Science and Engineering at SRM University–AP, India. She holds a Ph.D. from the National Institute of Technology, Warangal. Her research interests include Big Data, Data Mining, Artificial Intelligence, and Machine Learning. She has published seven patents, several articles in SCI/Scopus-indexed journals, conference proceedings, and a couple of book chapters. She has over 15 years of teaching experience.

Innehållsförteckning

Preface. 1. Revolutionizing IoMT with Blockchain: Securing the Future of Healthcare. 2. Optimizing Blockchain Integration for Secure and Scalable Internet of Medical Things in Healthcare Applications. 3. Enhancing Security of Medical Images Using DNA Cryptography and RSA Encryption. 4. Secure Transmission of Image Data for Autism Spectrum Disorder Diagnostics and Analysis. 5. Enhancing Data Security and Preserving Privacy in Visual Media with Intelligent Data Recoverable Techniques. 6. FLEX-HAND: Flexible Lightweight Handover Authentication for Next-Gen Driving. 7. Secure Real-Time Payment Fraud Detection Using Quantum Homomorphic Encryption Techniques. 8. Intelligent Systems for Real-Time Detection of Fraudulent Activities in Digital Financial Transactions. 9. Privacy-Preserving Fingerprint Authentication Using SaDeXNet and Fully Homomorphic Encryption. 10. ECC-Driven Lightweight Iris Recognition for Blockchain and IoT Ecosystems 11. Federated Learning Techniques for Privacy Enhanced Data Mining. 12. Federated Learning Frameworks with Privacy Protection for Predicting Heart Disease: Horizontal, Vertical, and Hybrid Strategies. 13. Dynamic Client Selection and Privacy Preserving Federated Learning Framework for Retinal Disease Detection. 14. EEG-based Automatic Personal Identification: Cybersecurity Perspectives in IoT-Enabled Smart Cities. 15. Privacy-Preserving Personalized Summarization via Federated Transformers. References. Index.