Ben Othman Soufiane - Böcker

Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI.

The healthcare sphere is becoming more interconnected, intelligent and data driven. The management of healthcare data - and developments in the devices, technologies and systems used to obtain, interpret, store and access it - is a key theme for many researchers in healthcare and technology fields. Sensors and IoT devices are increasingly used to obtain better information about patients' health, machine learning and numerical optimization techniques are being deployed in interpreting medical information, and secure healthcare records and telemedicine approaches are needed to enable clinicians and patients to access data remotely. All these technological advances fall under the umbrella term of Healthcare 4.0.This book explores the ideas and practices around utilizing IoT integration within the healthcare ecosystem to improve patient diagnosis, monitoring, and treatment, using machine learning and optimization to develop proactive healthcare systems. The book aims to provide both the necessary theoretical foundations for a sound understanding of the topic, and experimental case studies to show how Healthcare 4.0 applies to real-world situations. Coverage includes data modelling, information discovery, prediction, smart healthcare, transparency in governance, and auditing.The book's editors have brought together an international team of experts to discuss and share their opinions on Healthcare 4.0, evaluate existing solutions and provide real-world, practical case studies. Their intention has been to provide an interesting resource for researchers in the field of computer science, computer engineering, healthcare technology, computer vision, pattern recognition, machine learning, IoT, AI, signal processing, blockchain and big data and those in related disciplines.

This book is an essential resource that delves into the transformative potential of augmented reality (AR) and virtual reality (VR) within the healthcare industry.