Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics
Theories and Applications
(Sprache: Englisch)
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,...
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Klappentext zu „Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics “
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.
Inhaltsverzeichnis zu „Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics “
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.Autoren-Porträt
Haruna Chiroma received B.Tech., M.Sc., and Ph.D. degrees in computer science from Abubakar Tafawa Balewa University, Bayero University Kano and University of Malaya, respectively. He is an associate editor for Telecommunication, Computing, Electronic and Control Journal and an editorial board member for Recent advances in Computer Science and Communications. He has published over 100 academic articles, and edited the book Advances on Computational Intelligence in Energy- The Applications of Nature-Inspired & Metaheuristic Algorithms in Energy. He has been a technical programme committee member for more than 20 international conferences. Presently, Dr Chiroma is supervising 7 M.Sc. students and 2 Ph.D., 3 M.Sc. completed thesis at Abubakar Tafawa Balewa University, Bauchi, Nigeria as visiting senior lecturer and a senior lecturer at the Federal College of Education (Technical), Gombe, Nigeria.
Bibliographische Angaben
- 2021, 1st ed. 2021, VI, 315 Seiten, 68 farbige Abbildungen, Masse: 16,1 x 24,7 cm, Gebunden, Englisch
- Herausgegeben: Haruna Chiroma, Shafi'i M. Abdulhamid, Philippe Fournier-Viger, Nuno M. Garcia
- Verlag: Springer, Berlin
- ISBN-10: 303066287X
- ISBN-13: 9783030662875
Sprache:
Englisch
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