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Machine learning and data mining for...

Chiroma, Haruna.

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Machine learning and data mining for emerging trend in cyber dynamics = theories and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning and data mining for emerging trend in cyber dynamics/ edited by Haruna Chiroma ... [et al.].
其他題名:	theories and applications /
其他作者:	Chiroma, Haruna.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	vii, 315 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-030-66288-2
ISBN:	9783030662882

Machine learning and data mining for emerging trend in cyber dynamics = theories and applications /
Machine learning and data mining for emerging trend in cyber dynamicstheories and applications /[electronic resource] :edited by Haruna Chiroma ... [et al.]. - Cham :Springer International Publishing :2021. - vii, 315 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783030662882

Standard No.: 10.1007/978-3-030-66288-2doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .M33 2021

Dewey Class. No.: 006.31

Machine learning and data mining for emerging trend in cyber dynamics = theories and applications /
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505 0 $a 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.
520 $a 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.
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650 0 $a Data mining. $3 562972
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