Adversarial Machine Learning [E-Book] : Attack Surfaces, Defence Mechanisms, Learning Theories in Artificial Intelligence / by Aneesh Sreevallabh Chivukula, Xinghao Yang, Bo Liu, Wei Liu, Wanlei Zhou.
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the late...
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Full text |
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Personal Name(s): | Sreevallabh Chivukula, Aneesh, author |
Liu, Bo, author / Liu, Wei, author / Yang, Xinghao, author / Zhou, Wanlei, author | |
Edition: |
1st edition 2023. |
Imprint: |
Cham :
Springer,
2023
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Physical Description: |
XIX, 302 pages (online resource) |
Note: |
englisch |
ISBN: |
9783030997724 |
DOI: |
10.1007/978-3-030-99772-4 |
Subject (LOC): |
- Adversarial Machine Learning
- Adversarial Deep Learning
- Security and Privacy in Adversarial Learning
- Game-Theoretical Attacks with Adversarial Deep Learning Models
- Physical Attacks in the Real World
- Adversarial Defense Mechanisms
- Adversarial Learning for Privacy Preservation.