TY - BOOK AU - Ouaissa,Mariya AU - Boulouard,Zakaria AU - Ouaissa,Mariyam AU - Khan,Inam Ullah AU - Kaosar,Mohammed TI - Big Data Analytics and Computational Intelligence for Cybersecurity T2 - Studies in Big Data, SN - 9783031057526 U1 - 620.00285 23 PY - 2022/// CY - Cham PB - Springer International Publishing, Imprint: Springer KW - Engineering-Data processing KW - Computational intelligence KW - Big data KW - Artificial intelligence KW - Cooperating objects (Computer systems) KW - Data Engineering KW - Computational Intelligence KW - Big Data KW - Artificial Intelligence KW - Cyber-Physical Systems N1 - New Advancements in Cybersecurity: A Comprehensive Survey -- CPSs Communication using 5G Network in the Light of Security -- A Survey on Security Aspects in RPL Protocol over IoT Network -- Analysis of Cybersecurity Risks and their Mitigation for Work-from-Home Tools and Techniques -- A Systemic Security and Privacy Review: Attacks and Prevention Mechanisms over IoT Layers -- Software-Defined Networking Security: A Comprehensive Review N2 - This book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks UR - https://doi.org/10.1007/978-3-031-05752-6 ER -