Bøger af Ahmed A. Abd El-Latif

In the age of social media dominance, a staggering amount of textual data floods our online spaces daily. While this wealth of information presents boundless opportunities for research and understanding human behavior, it also poses substantial challenges. The sheer volume of data overwhelms traditional processing methods, and harnessing its potential requires sophisticated tools. Furthermore, the need for ensuring data security and mitigating risks in the digital realm has never been more pressing. Academic scholars, researchers, and professionals grapple with these issues daily, seeking innovative solutions to unlock the true value of multimedia data while safeguarding privacy and integrity. Recent Advancements in Multimedia Data Processing and Security: Issues, Challenges, and Techniques is a groundbreaking book that serves as a beacon of light amidst the sea of data-related challenges. It offers a comprehensive solution by bridging the gap between academic research and practical applications. By delving into topics such as deep learning, emotion recognition, and high-dimensional text clustering, it equips scholars and professionals with the innovative tools and techniques they need to navigate the complex landscape of multimedia data.

This book explores the intersection of cybersecurity and education technologies, providing practical solutions, detection techniques, and mitigation strategies to ensure a secure and protected learning environment in the face of evolving cyber threats.

This book gathers the proceedings of the International conference on Cybersecurity, Cybercrimes, and Smart Emerging Technologies, held on May 10¿11, 2022, in Riyadh, Saudi Arabia. The conference organized by the College of Computer Science of Prince Sultan University, Saudi Arabia. This book provides an opportunity to account for state-of-the-art works, future trends impacting cybersecurity, cybercrimes, and smart emerging technologies, that concern to organizations and individuals, thus creating new research opportunities, focusing on elucidating the challenges, opportunities, and inter-dependencies that are just around the corner. This book is helpful for students and researchers as well as practitioners. CCSET 2022 was devoted to advances in cybersecurity, cybercime, and smart emerging technologies. It was considered a meeting point for researchers and practitioners to implement advanced information technologies into various industries. There were 89 paper submissions from 25 countries. Each submission was reviewed by at least three chairs or PC members and 26 regular papers (30%) were accepted. Unfortunately, due to limitations of conference topics and edited volumes, the Program Committee was forced to reject some interesting papers, which did not satisfy these topics or publisher requirements.

This book presents state-of-the-art research on security and privacy- preserving for IoT and 5G networks and applications. The accepted book chapters covered many themes, including  traceability and tamper detection in IoT enabled waste management networks, secure Healthcare IoT Systems, data transfer accomplished by trustworthy nodes in cognitive radio, DDoS Attack Detection in Vehicular Ad-hoc Network (VANET) for 5G Networks, Mobile Edge-Cloud Computing, biometric authentication systems for IoT applications, and many other applicationsIt aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this particular area or those interested in grasping its diverse facets and exploring the latest advances on security and privacy- preserving for IoT and 5G networks. 

Computational Intelligence for Medical Internet of Things (MIoT) Applications: Machine Intelligence Applications for IoT in Healthcare explores machine intelligence techniques necessary for effective MIoT research and practice, taking a practical approach for practitioners and students entering the field. This book investigates advanced concepts and applications in the MIoT field, guiding readers through emerging developments and future trends. A wide range of international authors guide readers through advanced concepts, including deep learning, neural network, and big data analytic approaches for the classification, indexing, retrieval, analysis, and inferencing of healthcare data.