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This book provides a concise overview of the current state of the art in cybersecurity and shares novel and exciting ideas and techniques, along with specific cases demonstrating their practical application. It gathers contributions by both academic and industrial researchers, covering all aspects of cybersecurity and addressing issues in secure information systems as well as other emerging areas.
The content comprises high-quality research articles and reviews that promote a multidisciplinary approach and reflect the latest advances, challenges, requirements and methodologies. Thus, the book investigates e.g. security vulnerabilities, cybercrime, and privacy issues related to big data analysis, as well as advances in digital forensics, secure smart city services, and risk mitigation strategies for devices employing cyber-physical systems.
Given its scope, the book offers a valuable resource for students, researchers, IT professionals and providers, citizens, consumers and policymakers involved or interested in the modern security procedures needed to protect our information and communication resources. Its goal is to foster a community committed to further research and education, and one that can also translate its findings into concrete practices.
Dr. Elhoseny is a TPC Member or Reviewer in 30+ International Conferences and Workshops. Furthermore, he has been reviewing papers for 20+ International Journals including IEEE Communications Magazine, IEEE Transactions on Intelligent Transportation Systems, IEEE Sensors Letters, IEEE Communication Letters, Elsevier Computer Communications, Computer Networks, Sustainable Cities and Society, Wireless Personal Communications, and Expert Systems with Applications.
Security and Privacy in Smart City Applications and Services: Opportunities and Challenges.- A Lightweight Multi-Level Encryption Model for IoT Applications.- An Efficient Image Encryption Scheme based on Signcryption Technique with Adaptive Elephant Herding Optimization.- Time Split based Pre-processing with a Data-driven Approach for Malicious URL Detection; Optimal Wavelet Coefficients Based Steganography for Image Security with Secret Sharing Cryptography Model.- Deep learning Framework for Cyber Threat Situational Awareness based on Email and URL Data Analysis.- Application of Deep Learning Architectures for Cyber security.-Improved DGA Domain Names Detection and Categorization using Deep learning Architectures with Classical Machine learning Algorithms.- Secure Data Transmission through Reliable Vehicles in VANET using Optimal Lightweight Cryptography.- Some specific examples of attacks on information systems and smart cities applications.- Clustering Based Cybersecurity Model for Cloud Data.- A Detailed Investigation and Analysis of Deep Learning Architectures and Visualization Techniques for Malware Family Identification.- Design and Implementation of a Research and Education Cybersecurity Operations Center.
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