This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large number?of algorithms are succinctly described, along with a presentation of their?strengths and weaknesses.
The authors also cover algorithms that address?different kinds of problems of interest with single and multiple time series?data and multi-dimensional data. New ensemble anomaly detection?algorithms are? described, utilizing the benefits provided by diverse?algorithms, each of which work well on some kinds of data.
?With advancements in technology and the extensive use of the internet as?a medium for communications and commerce, there has been a?tremendous increase in the threats faced by individuals and organizations?from attackers and criminal entities. Variations in the observable behaviors?of individuals (from others and from their own past behaviors) have been?found to be useful in predicting potential problems of various kinds. Hence?computer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets.
?This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies.
Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation) Ebook
Author:
File Size: 3315 KB
Print Length: 239 pages
Publisher: Springer; 1st ed. 2017 edition (November 18, 2017)
Publication Date: November 18, 2017
Language: English
