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Adversarial Machine Learning
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Table of Contents

  • List of Figures
  • Preface
  • Acknowledgments
  • Introduction
  • Machine Learning Preliminaries
  • Categories of Attacks on Machine Learning
  • Attacks at Decision Time
  • Defending Against Decision-Time Attacks
  • Data Poisoning Attacks
  • Defending Against Data Poisoning
  • Attacking and Defending Deep Learning
  • The Road Ahead
  • Bibliography
  • Authors' Biographies
  • Index

About the Author

Yevgeniy Vorobeychik is an Assistant Professor of Computer Science, Computer Engineering, and Biomedical Informatics at Vanderbilt University. Previously, he was a Principal Research Scientist at Sandia National Laboratories. Between 2008 and 2010, he was a post doctoral research associate at the University of Pennsylvania Computer and Information Science department. He received Ph.D. (2008) and M.S.E. (2004) degrees in Computer Science and Engineering from the University of Michigan, and a B.S. degree in Computer Engineering from Northwestern University. His work focuses on game theoretic modeling of security and privacy, adversarial machine learning, algorithmic and behavioral game theory and incentive design, optimization, agent-based modeling, complex systems, network science, and epidemic control. Dr. Vorobeychik received an NSF CAREER award in 2017, and was invited to give an IJCAI-16 early career spotlight talk. He was nominated for the 2008 ACM Doctoral Dissertation Award and received honorable mention for the 2008 IFAAMAS Distinguished Dissertation Award.

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