Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation) - Tapa dura

Mohan, Chilukuri K.; Huang, HuaMing; Mehrotra, Kishan G.

 
9783319675244: Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)
Tapa dura
ISBN 10: 3319675249 ISBN 13: 9783319675244
Editorial: Springer, 2018

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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 theirown 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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"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
3319675249
ISBN 13 
9783319675244
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
240
Contacto del fabricante
ROXIO
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
22391
Alemania

Otras ediciones populares con el mismo título

9783319884455: Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)

Edición Destacada

ISBN 10:  331988445X ISBN 13:  9783319884455
Editorial: Springer, 2019
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