Implementing Generative AI in Cybersecurity (Paperback)

Idioma: inglés

Editorial: Independently Published, 2024

9798327273948

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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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Paperback. In an era where cyber threats are becoming increasingly sophisticated, "Implementing Generative AI in Cybersecurity: Techniques, Tools, and Case Studies" serves as a comprehensive guide for professionals and enthusiasts looking to leverage the power of generative AI to bolster their cybersecurity defenses. This book delves into the intersection of two rapidly evolving fields-artificial intelligence and cybersecurity-providing readers with the knowledge and tools necessary to stay ahead of cyber adversaries. The book begins with an introduction to generative AI and its pivotal role in transforming cybersecurity. It covers the basics of generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), explaining their mechanics and applications in creating synthetic data, enhancing training datasets, and anonymizing sensitive information. Moving into practical applications, the book explores how generative AI can be used for data augmentation and synthesis to improve the accuracy and robustness of machine learning models used in threat detection and incident response. Readers will learn about the latest techniques for detecting and defending against adversarial attacks, ensuring their AI systems remain resilient against sophisticated manipulations. A significant portion of the book is dedicated to real-world case studies, demonstrating how leading organizations in various sectors-finance, healthcare, and government-have successfully implemented generative AI solutions to enhance their cybersecurity posture. These case studies provide valuable insights into the practical challenges and strategies for integrating AI technologies into existing security frameworks. Deepfake detection and prevention, a crucial aspect of modern cybersecurity, is also covered in depth. The book outlines state-of-the-art detection techniques and countermeasures to combat the rising threat of synthetic media used for malicious purposes. The use of natural language processing (NLP) in security is another focal point, highlighting its applications in phishing detection, secure communication analysis, and threat intelligence. Ethical considerations, privacy concerns, and the regulatory landscape are discussed to provide a holistic view of the challenges and responsibilities involved in deploying AI-driven cybersecurity solutions. "Implementing Generative AI in Cybersecurity: Techniques, Tools, and Case Studies" is an essential resource for cybersecurity professionals, AI practitioners, and anyone interested in the future of digital security, offering practical guidance and actionable insights to navigate the complexities of integrating generative AI into cybersecurity strategies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

N° de ref. del artículo 9798327273948

Título
Implementing Generative AI in Cybersecurity (Paperback)
Autor
Anand Vemula
Editorial
Independently Published
Año de publicación
2024
Estado
new
Encuadernación
Paperback
Idioma
inglés
ISBN 13
9798327273948

CitiRetail

Stevenage, Reino Unido

Vendedor de 5 estrellas

Vendedor de IberLibro desde 29 de junio de 2022

Tarifas de envío de Reino Unido a Estados Unidos de America

ArtículoDe 7 a 14 días hábilesDe 7 a 60 días hábiles
Primer artículoEUR 44,07EUR 44,07
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