Description: The LLM Security Handbook by Anand Vemula In a world increasingly powered by artificial intelligence, Large Language Models (LLMs) are emerging as powerful tools capable of generating human-quality text, translating languages, and writing different creative content. However, this power comes with hidden risks. This book dives deep into the world of LLM security, providing a comprehensive guide for developers, security professionals, and anyone interested in harnessing the potential of LLMs responsibly.Part 1: Understanding the LandscapeThe book starts by unpacking the inner workings of LLMs and explores how these models can be misused to generate harmful content or leak sensitive data. We delve into the concept of LLM bias, highlighting how the data used to train these models can influence their outputs. Through real-world scenarios and case studies, the book emphasizes the importance of proactive security measures to mitigate these risks.Part 2: Building Secure LLM ApplicationsThe core of the book focuses on securing LLM applications throughout their development lifecycle. We explore the Secure Development Lifecycle (SDLC) for LLMs, emphasizing secure data acquisition, robust model testing techniques, and continuous monitoring strategies. The book delves into MLOps security practices, highlighting techniques for securing model repositories, implementing anomaly detection, and ensuring the trustworthiness of LLM models.Part 3: Governance and the Future of LLM SecurityWith the rise of LLMs, legal and ethical considerations come to the forefront. The book explores data privacy regulations and how to ensure responsible AI development practices. We discuss the importance of explainability and transparency in LLM decision-making for building trust and addressing potential biases.Looking ahead, the book explores emerging security threats and emphasizes the importance of continuous improvement and collaboration within the LLM security community. By proactively addressing these challenges, we can ensure a secure future for LLM applications.This book empowers readers with the knowledge and best practices to navigate the exciting yet complex world of LLM security. FORMAT Paperback CONDITION Brand New Details ISBN Author Anand Vemula Pages 70 Publisher Independently Published Year 2024 ISBN-13 9798326259660 Format Paperback Publication Date 2024-05-21 Imprint Independently Published Subtitle Building Trustworthy AI Applications Audience General We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:160652734;
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ISBN-13: 9798326259660
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