
Advanced Techniques for Anomaly Detection
Beyond the Basics
CRC Press
1st Edition
Published on 9. May 2025
Book
Hardback
188 pages
978-1-032-72930-5 (ISBN)
Description
This book is a comprehensive guide that explores the latest developments in anomaly detection techniques across a range of fields, including cybersecurity, finance, image processing, sensor networks, social network analysis, health systems, and IoT systems. With 6 chapters covering various topics such as deep learning-based anomaly detection, feature selection and extraction techniques, ensemble methods, and evaluation metrics, this book offers a comprehensive understanding of advanced anomaly detection techniques and their applications in different fields. This book will be an excellent resource for researchers, practitioners, and students interested in anomaly detection and its applications in various domains.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Academic and Postgraduate
Illustrations
5 s/w Tabellen, 42 s/w Abbildungen, 42 s/w Zeichnungen
5 Tables, black and white; 42 Line drawings, black and white; 42 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 15 mm
Weight
461 gr
ISBN-13
978-1-032-72930-5 (9781032729305)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
05/2025
1st Edition
CRC Press
€73.99
Available for download

E-Book
05/2025
1st Edition
CRC Press
€73.99
Available for download
Persons
Abdul Wahid, PhD, Department of Computer Science and Engineering, Indian Institute of Information Technology, Dharwad, India.
Praveen Kumar Donta, PhD, Department of Computer and Systems Sciences, Stockholm, Sweden.
Praveen Kumar Donta, PhD, Department of Computer and Systems Sciences, Stockholm, Sweden.
Content
Chapter 1 : Anomaly Detection in Carbon Sequestration: Advancements, Challenges, and Future Directions. Chapter 2: Intelligent Anomaly Detection in Social Media. Chapter 3: Anomaly Detection in Health-Care. Chapter 4: Safeguarding Health in the Cloud: A Cutting-Edge Machine Learning Intrusion Detection. Chapter 5: Deep Learning for Anomaly Detection in IoT Time Series. Chapter 6: Pen Ink Analysis in Handwritten Document Forensics: Classification and Current Trends