“This book presents the interesting topic of anomaly detection for a very broad audience. … The presentation is really useful: for each technique, some motivation is given, including real-life situations, a comprehensible formalization, and pros and cons, which gives readers an idea of how useful the technique will be in practice. … Probably the most important contribution of the book is its citations and references for further reading, which may help casual readers better understand each technique … .” (Santiago Escobar, Computing Reviews, January, 2019)​

• 1 Introduction.- 2 Anomaly Detection.- 3 Distance-based Anomaly Detection Approaches.- 4 Clustering-based Anomaly Detection Approaches.- 5 Model-based Anomaly Detection Approaches.- 6 Distance and Density Based Approaches.- 7 Rank Based Approaches.- 8 Ensemble Methods.- 9 Algorithms for Time Series Data.- Datasets for Evaluation.- Datasets for Time Series Experiments.

“This book presents the interesting topic of anomaly detection for a very broad audience. … The presentation is really useful: for each technique, some motivation is given, including real-life situations, a comprehensible formalization, and pros and cons, which gives readers an idea of how useful the technique will be in practice. … Probably the most important contribution of the book is its citations and references for further reading, which may help casual readers better understand each technique … .” (Santiago Escobar, Computing Reviews, January, 2019)​

• 1 Introduction.- 2 Anomaly Detection.- 3 Distance-based Anomaly Detection Approaches.- 4 Clustering-based Anomaly Detection Approaches.- 5 Model-based Anomaly Detection Approaches.- 6 Distance and Density Based Approaches.- 7 Rank Based Approaches.- 8 Ensemble Methods.- 9 Algorithms for Time Series Data.- Datasets for Evaluation.- Datasets for Time Series Experiments.

“This book presents the interesting topic of anomaly detection for a very broad audience. … The presentation is really useful: for each technique, some motivation is given, including real-life situations, a comprehensible formalization, and pros and cons, which gives readers an idea of how useful the technique will be in practice. … Probably the most important contribution of the book is its citations and references for further reading, which may help casual readers better understand each technique … .” (Santiago Escobar, Computing Reviews, January, 2019)​

• 1 Introduction.- 2 Anomaly Detection.- 3 Distance-based Anomaly Detection Approaches.- 4 Clustering-based Anomaly Detection Approaches.- 5 Model-based Anomaly Detection Approaches.- 6 Distance and Density Based Approaches.- 7 Rank Based Approaches.- 8 Ensemble Methods.- 9 Algorithms for Time Series Data.- Datasets for Evaluation.- Datasets for Time Series Experiments.