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Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics : Theories and Applications / edited by Haruna Chiroma, Shafi'i M. Abdulhamid, Philippe Fournier-Viger, Nuno M. Garcia.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Language:
- English
- Subjects (All):
- Cooperating objects (Computer systems).
- Data mining.
- Quantitative research.
- Machine learning.
- Cyber-Physical Systems.
- Data Mining and Knowledge Discovery.
- Data Analysis and Big Data.
- Machine Learning.
- Local Subjects:
- Cyber-Physical Systems.
- Data Mining and Knowledge Discovery.
- Data Analysis and Big Data.
- Machine Learning.
- Physical Description:
- 1 online resource (VI, 315 pages) : 120 illustrations, 68 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.
- Contents:
- Generative Adversarial Network for the Detection of Ransomware in Cyber Dynamics
- Deep Learning for Blockchain Technologies: A Survey and Research Directions
- Deep Recurrent Neural Network for the Enhancement of Resource Allocation in Edge Computing
- Recommender Systems in the Next Generation Cloud Architectures
- Collusion Detection in the Internet of Vehicles Environment via Machine Learning Algorithms
- Mobile Cloud Computing Security Strategies Using Machine Learning Algorithms
- Resilient Edge Computing Devices Using Federated Learning Technique
- DeepFake: A Panacea for New Generation Simulated Videos
- Machine Learning-Based Malware Detection Systems in a Cyber-Physical Systems
- Support Vector Machine-Based Crypto-Locker Ransomware Attacks Detection with Grey-Wolf Optimization
- A Survey of Algorithms for Analysing Graph Data in the Cloud
- A Survey of Sequence Prediction Models to Predict Behaviour of Dynamic Systems
- Finding High Utility Patterns to Detect Network Attacks
- Authorship Attribution and User Profile Inference in Social Networks
- Deep Convolutional Neural Network for Data Analytics in the Cyber Dynamics.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-66288-2
- 9783030662882
- Access Restriction:
- Restricted for use by site license.
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