Book contents
- Frontmatter
- Contents
- List of Symbols
- Acknowledgments
- Part I Overview of Adversarial Machine Learning
- Part II Causative Attacks on Machine Learning
- Part III Exploratory Attacks on Machine Learning
- Part IV Future Directions in Adversarial Machine Learning
- Part V Appendixes
- Appendix A: Background for Learning and Hyper-Geometry
- Appendix B: Full Proofs for Hypersphere Attacks
- Appendix C: Analysis of SpamBayes
- Appendix D: Full Proofs for Near-Optimal Evasion
- Glossary
- References
- Index
Appendix D: Full Proofs for Near-Optimal Evasion
from Part V - Appendixes
Published online by Cambridge University Press: 14 March 2019
- Frontmatter
- Contents
- List of Symbols
- Acknowledgments
- Part I Overview of Adversarial Machine Learning
- Part II Causative Attacks on Machine Learning
- Part III Exploratory Attacks on Machine Learning
- Part IV Future Directions in Adversarial Machine Learning
- Part V Appendixes
- Appendix A: Background for Learning and Hyper-Geometry
- Appendix B: Full Proofs for Hypersphere Attacks
- Appendix C: Analysis of SpamBayes
- Appendix D: Full Proofs for Near-Optimal Evasion
- Glossary
- References
- Index
- Type
- Chapter
- Information
- Adversarial Machine Learning , pp. 285 - 294Publisher: Cambridge University PressPrint publication year: 2019