صورة الغلاف

Security and Privacy in Federated Learning

In this book, the authors highlight the latest research findings on the security and privacy of federated learning systems. The main attacks and counterattacks in this booming field are presented to readers in connection with inference, poisoning, generative adversarial networks, differential privac...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Yu, Shui (مؤلف), Cui, Lei (مؤلف)
مؤلف مشترك: SpringerLink (Online service)
التنسيق: الكتروني كتاب الكتروني
اللغة:الإنجليزية
منشور في: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
الطبعة:1st ed. 2023.
سلاسل:Digital Privacy and Security,
الموضوعات:
Data protection.
Data protection > Law and legislation.
Artificial intelligence.
Data and Information Security.
Privacy.
Artificial Intelligence.
الوصول للمادة أونلاين:https://doi.org/10.1007/978-981-19-8692-5
الوسوم: إضافة وسم
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جدول المحتويات:
  • Chapter 1. Introduction of Federated Learning
  • Chapter 2. Inference Attacks and Counter Attacks in Federated Learning
  • Chapter 3. Poisoning Attacks and Counter Attacks in Federated Learning
  • Chapter 4. GAN Attacks and Counter Attacks in Federated Learning
  • Chapter 5. Differential Privacy in Federated Learning
  • Chapter 6. Secure Multi-Party Computation in Federated Learning
  • Chapter 7. Secure Data Aggregation in Federated Learning
  • Chapter 8. Anonymous Communication and Shuffle Model in Federated Learning
  • Chapter 9. The Future Work.

مواد مشابهة