LEADER 04312nam  22006495  450 
001 9910483360403321
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010   $a3-030-66288-8
024 7 $a10.1007/978-3-030-66288-2
035   $a(CKB)4100000011867249
035   $a(MiAaPQ)EBC6533347
035   $a(Au-PeEL)EBL6533347
035   $a(OCoLC)1244805799
035   $a(PPN)255294824
035   $a(DE-He213)978-3-030-66288-2
035   $a(EXLCZ)994100000011867249
100   $a20210401d2021      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMachine Learning and Data Mining for Emerging Trend in Cyber Dynamics $eTheories and Applications /$fedited by Haruna Chiroma, Shafi?i M. Abdulhamid, Philippe Fournier-Viger, Nuno M. Garcia
205   $a1st ed. 2021.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021.
215   $a1 online resource (315 pages) $cillustrations
225 1 $aComputer Science Series
311 08$a3-030-66287-X 
320   $aIncludes bibliographical references.
327   $aGenerative 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.
330   $aThis book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.
410  0$aComputer Science Series
606   $aCooperating objects (Computer systems)
606   $aData mining
606   $aQuantitative research
606   $aMachine learning
606   $aCyber-Physical Systems
606   $aData Mining and Knowledge Discovery
606   $aData Analysis and Big Data
606   $aMachine Learning
615  0$aCooperating objects (Computer systems).
615  0$aData mining.
615  0$aQuantitative research.
615  0$aMachine learning.
615 14$aCyber-Physical Systems.
615 24$aData Mining and Knowledge Discovery.
615 24$aData Analysis and Big Data.
615 24$aMachine Learning.
676   $a354.81150006
702   $aChiroma$b Haruna
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483360403321
996   $aMachine learning and data mining for emerging trend in cyber dynamics$92814479
997   $aUNINA