Note: Intro -- Preface -- Contents -- Author Biography -- List of Figures -- List of Tables -- 1 Adversarial Machine Learning -- 1.1 Adversarial Learning Frameworks -- 1.1.1 Adversarial Algorithms Comparisons -- 1.2 Adversarial Security Mechanisms -- 1.2.1 Adversarial Examples Taxonomies -- 1.3 Stochastic Game Illustration in Adversarial Deep Learning -- 2 Adversarial Deep Learning -- 2.1 Learning Curve Analysis for Supervised Machine Learning -- 2.2 Adversarial Loss Functions for Discriminative Learning -- 2.3 Adversarial Examples in Deep Networks -- 2.4 Adversarial Examples for Misleading Classifiers -- 2.5 Generative Adversarial Networks -- 2.6 Generative Adversarial Networks for Adversarial Learning -- 2.6.1 Causal Feature Learning and Adversarial Machine Learning -- 2.6.2 Explainable Artificial Intelligence and Adversarial Machine Learning -- 2.6.3 Stackelberg Game Illustration in Adversarial Deep Learning -- 2.7 Transfer Learning for Domain Adaptation -- 2.7.1 Adversarial Examples in Transfer learning -- 2.7.2 Adversarial Examples in Domain Adaptation -- 2.7.3 Adversarial Examples in Cybersecurity Domains -- 3 Adversarial Attack Surfaces -- 3.1 Security and Privacy in Adversarial Learning -- 3.1.1 Linear Classifier Attacks -- 3.2 Feature Weighting Attacks -- 3.3 Poisoning Support Vector Machines -- 3.4 Robust Classifier Ensembles -- 3.5 Robust Clustering Models -- 3.6 Robust Feature Selection Models -- 3.7 Robust Anomaly Detection Models -- 3.8 Robust Task Relationship Models -- 3.9 Robust Regression Models -- 3.10 Adversarial Machine Learning in Cybersecurity -- 3.10.1 Sensitivity Analysis of Adversarial Deep Learning -- 4 Game Theoretical Adversarial Deep Learning -- 4.1 Game Theoretical Learning Models -- 4.1.1 Fundamentals of Game Theory -- 4.1.2 Game Theoretical Data Mining -- 4.1.3 Cost-Sensitive Adversaries. , 4.1.4 Adversarial Training Strategies -- 4.2 Game Theoretical Adversarial Learning -- 4.2.1 Multilevel and Multi-stage Optimization in Game Theoretical Adversarial Learning -- 4.3 Game Theoretical Adversarial Deep Learning -- 4.3.1 Overall Structure of Learning Model in Variational Game -- 4.3.2 The Differences Between Our Method and GANs -- 4.3.3 Comparisons of Game Theoretical Adversarial Deep Learning Models -- 4.3.4 Comparisons Between Single Play Attacks and Multiple Play Attacks on Custom Loss Functions -- 4.3.5 Parallel Machines in Reduced Games -- 4.4 Stochastic Games in Predictive Modeling -- 4.4.1 Computational Learning Theory Frameworks to Analyze Game Theoretical Learning Algorithms -- 4.4.2 Game Theoretical Adversarial Deep Learning Algorithms in Information Warfare Applications -- 4.4.3 Game Theoretical Adversarial Deep Learning Algorithms in Cybersecurity Applications -- 4.5 Robust Game Theory in Adversarial Learning Games -- 4.5.1 Existence and Uniqueness of Game Theoretical Equilibrium Solutions -- 4.5.2 Optimal Control Theory and Robust Game Theory -- 5 Adversarial Defense Mechanisms for Supervised Learning -- 5.1 Securing Classifiers Against Feature Attacks -- 5.2 Adversarial Classification Tasks with Regularizers -- 5.3 Adversarial Reinforcement Learning -- 5.3.1 Game Theoretical Adversarial Reinforcement Learning -- 5.4 Computational Optimization Algorithmics for Game Theoretical Adversarial Learning -- 5.4.1 Game Theoretical Learning -- 5.4.1.1 Randomization Strategies in Game Theoretical Adversarial Learning -- 5.4.1.2 Adversarial Deep Learning in Robust Games -- 5.4.1.3 Robust Optimization in Adversarial Learning -- 5.4.2 Generative Learning -- 5.4.2.1 Deep Generative Models for Game Theoretical Adversarial Learning -- 5.4.2.2 Mathematical Programming in Game Theoretical Adversarial Learning. , 5.4.2.3 Low-Rank Approximations in Game Theoretical Adversarial Learning -- 5.4.2.4 Relative Distribution Methods in Adversarial Deep Learning -- 5.5 Defense Mechanisms in Adversarial Machine Learning -- 5.5.1 Defense Mechanisms in Adversarial Deep Learning -- 5.5.2 Explainable Artificial Intelligence in Adversarial Deep Learning -- 6 Physical World Adversarial Attacks on Images and Texts -- 6.1 Adversarial Attacks on Images -- 6.1.1 Gradient-Based Attack -- 6.1.2 Score-Based Attack -- 6.1.3 Decision-Based Attack -- 6.1.4 Transformation-Based Attack -- 6.2 Adversarial Attacks on Texts -- 6.2.1 Character-Level Attack -- 6.2.2 Sentence-Level Attack -- 6.2.3 Word-Level Attack -- 6.2.4 Multilevel Attack -- 6.3 Spam Filtering -- 6.3.1 Text Spam -- 6.3.2 Image Spam -- 6.3.3 Biometric Spam -- 7 Adversarial Perturbation for Privacy Preservation -- 7.1 Adversarial Perturbation for Privacy Preservation -- 7.1.1 Visual Data Privacy Model -- 7.1.2 Privacy Protection Mechanisms Using Adversarial Perturbations -- 7.1.2.1 File-Level Privacy Protection -- 7.1.2.2 Object-Level Privacy Protection -- 7.1.2.3 Feature-Level Privacy Protection -- 7.1.3 Discussion and Future Works -- Correction to: Adversarial Machine Learning -- References.