Generative AI Security: Theories and Practices (Hardback or Cased Book)

Generative AI Security: Theories and Practices (Hardback or Cased Book)

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Generative AI Security: Theories and Practices (Hardback or Cased Book)

In today’s digital age, the use of artificial intelligence is becoming increasingly prevalent in various industries. One particular area where AI is making significant strides is in generative AI, which involves creating new data or content based on existing patterns. While this technology holds great promise for innovation and creativity, it also raises concerns about security and privacy.

This comprehensive book delves into the theories and practices of generative AI security, providing a thorough examination of the potential risks and vulnerabilities associated with this emerging technology. From deep learning algorithms to adversarial attacks, the authors explore the various threats that can compromise the security of generative AI systems.

Drawing on real-world examples and case studies, the book offers practical guidance on how organizations can enhance the security of their generative AI applications. Topics covered include encryption techniques, anomaly detection, and secure data sharing protocols. Additionally, the authors discuss ethical considerations and regulatory frameworks that can help mitigate the risks associated with generative AI.

Whether you are a cybersecurity professional, AI researcher, or industry practitioner, Generative AI Security: Theories and Practices is a must-read for anyone looking to understand the security implications of this cutting-edge technology. This hardback or cased book provides a comprehensive overview of the latest advancements in generative AI security, offering valuable insights for safeguarding data and ensuring the integrity of AI systems.
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