Wadii Boulila (63 results)

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Taschenbuch. Condition: Neu. Decision Making and Security Risk Management for IoT Environments | Wadii Boulila (u. a.) | Taschenbuch | Advances in Information Security | viii | Englisch | 2025 | Springer | EAN 9783031475924 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains contemporary research that outlines and addresses security, privacy challenges and decision-making in IoT environments. The authors provide a variety of subjects related to the following Keywords: IoT, security, AI, deep learning, federated learning, intrusion detection systems, and distributed computing paradigms. This book also offers a collection of the most up-to-date research, providing a complete overview of security and privacy-preserving in IoT environments. It introduces new approaches based on machine learning that tackles security challenges and provides the field with new research material that's not covered in the primary literature.The Internet of Things (IoT) refers to a network of tiny devices linked to the Internet or other communication networks. IoT is gaining popularity, because it opens up new possibilities for developing many modern applications. This would include smart cities, smart agriculture, innovative healthcare services and more. The worldwide IoT market surpassed $100 billion in sales for the first time in 2017, and forecasts show that this number might reach $1.6 trillion by 2025. However, as IoT devices grow more widespread, threats, privacy and security concerns are growing. The massive volume of data exchanged highlights significant challenges to preserving individual privacy and securing shared data. Therefore, securing the IoT environment becomes difficult for research and industry stakeholders.Researchers, graduate students and educators in the fields of computer science, cybersecurity, distributed systems and artificial intelligence will want to purchase this book. It will also be a valuable companion for users and developers interested in decision-making and security risk management in IoT environments. …

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains contemporary research that outlines and addresses security, privacy challenges and decision-making in IoT environments. The authors provide a variety of subjects related to the following Keywords: IoT, security, AI, deep learning, federated learning, intrusion detection systems, and distributed computing paradigms. This book also offers a collection of the most up-to-date research, providing a complete overview of security and privacy-preserving in IoT environments. It introduces new approaches based on machine learning that tackles security challenges and provides the field with new research material that's not covered in the primary literature.The Internet of Things (IoT) refers to a network of tiny devices linked to the Internet or other communication networks. IoT is gaining popularity, because it opens up new possibilities for developing many modern applications. This would include smart cities, smart agriculture, innovative healthcare services and more. The worldwide IoT market surpassed $100 billion in sales for the first time in 2017, and forecasts show that this number might reach $1.6 trillion by 2025. However, as IoT devices grow more widespread, threats, privacy and security concerns are growing. The massive volume of data exchanged highlights significant challenges to preserving individual privacy and securing shared data. Therefore, securing the IoT environment becomes difficult for research and industry stakeholders.Researchers, graduate students and educators in the fields of computer science, cybersecurity, distributed systems and artificial intelligence will want to purchase this book. It will also be a valuable companion for users and developers interested in decision-making and security risk management in IoT environments. …

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Condition: New. 2024th edition NO-PA16APR2015-KAP.

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Hardcover. Condition: Brand New. 237 pages. 9.26x6.10x9.21 inches. In Stock.

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Condition: New. Examines the potential of edge computing and deep transfer learning, offering in-depth insights into how edge intelligence can be leveraged to enhance IoT and IIoT securityEmphasizes the development of lightweight and resource-efficient mod.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive exploration of the transformative impact of AI technologies across diverse fields. From revolutionizing healthcare diagnostics and advancing natural language processing for low-resource languages to enhancing software development and promoting environmental sustainability, this book explores the cutting-edge advancements and practical applications of generative AI and large language models (LLMs). With a focus on both opportunities and challenges, the book examines the architectural challenges of transformer-based models, the ethical implications of AI, and the importance of language-specific adaptations, particularly for low-resource languages like Arabic. It also highlights the role of AI in code development, multimodal applications, and its integration with intellectual property frameworks. This book is an essential resource for researchers, practitioners, and policymakers seeking to understand and harness the potential of AI to drive innovation and global progress.…

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Taschenbuch. Condition: Neu. International Conference on Smart Systems and Emerging Technologies | Edition 2024 | Anis Koubaa (u. a.) | Taschenbuch | Lecture Notes in Networks and Systems | xv | Englisch | 2025 | Springer | EAN 9783031912344 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Hardcover. Condition: Brand New. 317 pages. 9.25x6.10x9.21 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a groundbreaking compilation of cutting-edge research at the forefront of innovation, where artificial intelligence, machine learning, and advanced technologies converge to address real-world challenges with realistic solutions. This comprehensive book bridges theory and practice, offering transformative insights across diverse domains from healthcare and cybersecurity to smart cities and language processing.Dive into pioneering advancements in Technology such asArabic text-to-gloss machine translation,transformer-based image captioning, andGAN-enhanced privacy policiesfor constrained environments. Learn how deep learning revolutionizes cancer detection in medical imaging, optimizes traffic flow prediction, and refines speaker diarization in forensic audio. Immerse into ethical AI discussions, UAV navigation in GPS-denied terrains, and blockchain-secured voting systems, all while uncovering novel approaches to IoT security, cloud computing, and industrial efficiency.With contributions from leading researchers and practitioners, this book addresses critical topics likeAI-driven sentiment analysis for business intelligence,self-supervised graph neural networks, andethical implications of emerging technologies. Each chapter combines rigorous technical depth with actionable applications, making it an indispensable resource for researchers, engineers, and students eager to harness AI s potential in tackling modern global challenges.…

Taschenbuch. Condition: Neu. Neuware - Edge Intelligence: Advanced Deep Transfer Learning for IoT Security presents a comprehensive exploration into the critical intersection of cybersecurity, edge computing, and deep learning, offering practitioners, researchers, and cybersecurity professionals a definitive guide to protect IoT/IIoT systems. This book delves into the synergistic potential of edge computing and advanced machine/deep learning algorithms, providing insights into lightweight and resource-efficient models with a special focus on resource-constrained edge devices. The rapidly evolving nature of cyberattacks underscores the need for updated and integrated resources that address the intersection of cybersecurity, edge computing, and deep learning. The authors address this issue by offering practical insights, lightweight models, and proactive defense mechanisms tailored to the unique challenges of securing edge devices and networks. This book is not only written to provide its audience effective strategies to detect and mitigate network intrusions by leveraging edge intelligence and advanced deep transfer learning techniques but also to provide practical insights and implementation guidelines tailored to resource-constrained edge devices.…

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