Anomaly Detection Principles and Algorithms

Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Database Management, General Computing
Cover of the book Anomaly Detection Principles and Algorithms by Kishan G. Mehrotra, Chilukuri K. Mohan, HuaMing Huang, Springer International Publishing
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Author: Kishan G. Mehrotra, Chilukuri K. Mohan, HuaMing Huang ISBN: 9783319675268
Publisher: Springer International Publishing Publication: November 18, 2017
Imprint: Springer Language: English
Author: Kishan G. Mehrotra, Chilukuri K. Mohan, HuaMing Huang
ISBN: 9783319675268
Publisher: Springer International Publishing
Publication: November 18, 2017
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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