Buch, Englisch, 259 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 569 g
Reihe: Blockchain Technologies
Buch, Englisch, 259 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 569 g
Reihe: Blockchain Technologies
ISBN: 978-981-951393-2
Verlag: Springer
This book highlights the transformative synergy between Blockchain and Federated Learning in developing privacy-focused solutions for DeepFex . By leveraging the decentralized nature of blockchain alongside the privacy-preserving capabilities of federated learning, it offers a novel approach to combating the growing challenges of deepfake technology. The integration of these two cutting-edge technologies ensures data security, model integrity, and transparent collaboration, making it possible to detect and mitigate deepfakes in a scalable, ethical, and decentralized manner.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Technische Wissenschaften Bauingenieurwesen Gebäudesicherheit
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Kryptographie, Datenverschlüsselung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
Weitere Infos & Material
Introduction.- DeepFex: Detecting Deepfakes in the Digital Age.- Blockchain Technology Overview.- Federated Learning Basics.- Integrating Blockchain with Federated Learning.- Privacy and Security in DeepFex Solutions.- Real-World Applications and Use Cases.- Challenges, Ethics, and Regulatory Perspectives.- Future Directions.- Conclusion.




