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2024 | OriginalPaper | Buchkapitel

9. Utilizing Prompt Engineering to Operationalize Cybersecurity

verfasst von : Ken Huang, Grace Huang, Yuyan Duan, Ju Hyun

Erschienen in: Generative AI Security

Verlag: Springer Nature Switzerland

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Abstract

This chapter provides a comprehensive guide to prompt engineering techniques for cybersecurity operations. Core concepts establish a foundation for constructing specialized prompts that tap the power of GenAI for threat analysis, incident response, and security enhancement. Specific methods including few shot learning, Retrieval Augmented Generation, Chain of Thought, Tree of Thought, ReAct, and automated reasoning are elucidated to improve model capabilities on complex cybersecurity tasks. However, prudent practices are emphasized to address risks around adversarial attacks, biases, and ethical breaches. The chapter aims to equip security professionals with prompt engineering proficiencies to leverage GenAI responsibly based on principles of accountability and transparency.

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Vorheriges Kapitel From LLMOps to DevSecOps for GenAI

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Titel: Utilizing Prompt Engineering to Operationalize Cybersecurity
verfasst von: Ken Huang
Grace Huang
Yuyan Duan
Ju Hyun
Verlag: Springer Nature Switzerland
Buch: Generative AI Security
Print ISBN: 978-3-031-54251-0

Electronic ISBN: 978-3-031-54252-7

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-54252-7_9

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