GenAI Security

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This book is an essential guide for anyone looking to build secure and resilient generative AI applications. It provides actionable insights into identifying vulnerabilities and preventing attacks. This book is an essential guide for anyone looking to build secure and resilient generative AI applications. It provides actionable insights into identifying vulnerabilities and preventing attacks. Authored by security expert Paul Zenker, this book explores the critical aspects of securing GenAI systems across their lifecycle – design, development and operation. Through numerous practical examples, detailed illustrations of threat scenarios and application architectures, readers will gain a comprehensive understanding of potential risks. Step-by-step instructions cover techniques such as prompt injections, jailbreaks and other attack vectors, equipping readers with the skills to anticipate and mitigate threats effectively. This resource is ideal for developers, security professionals, AI researchers and organizations working with generative AI technologies. This book offers the tools and knowledge needed to create systems that can withstand sophisticated attacks in today’s high-stakes digital landscape.

Amazon

Pages: 156, Edition: 1, Hardcover, Chapman and Hall/CRC