Privacy and Security in FinTech, Healthcare, and Social Applications by Bojjagani, Sriramulu; Reddy, V. Dinesh; Saleti, Sumalatha;

Rövid leírás:

This book explores cybersecurity and privacy challenges in healthcare, FinTech, and intelligent systems. It covers blockchain-based protocols for IoMT and IoV, lightweight encryption, secure medical image sharing, DNA-RSA, quantum cryptography, AI-driven fraud analytics, and privacy-preserving federated learning.

Hosszú leírás:

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.

Tartalomjegyzék:

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.