Project Director

Xie, Mengjun

Department Examiner

Campbell, Curtis

Department

Dept. of Computer Science and Engineering

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in cybersecurity. It examines how these models are currently utilized for both offensive and defensive purposes, evaluates the ethical and regulatory implications of their deployment, and highlights ongoing efforts to mitigate associated risks. By synthesizing current research and real-world applications, this study aims to equip cybersecurity professionals, researchers, and policymakers with a nuanced understanding of LLMs’ impact on digital security, ultimately contributing to informed strategies for their responsible and secure use.

Acknowledgments

I would like to express my sincere gratitude to my thesis director, Dr. Mengjun Xie, for his unwavering support and guidance throughout this journey. His insight and encouragement were instrumental in bringing this work to fruition. I am also deeply thankful to Dr. Curtis Campbell for serving as a member of my committee and for offering valuable guidance and support from start to finish.

Degree

B. S.; An honors thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Bachelor of Science.

Date

5-2025

Subject

Artificial intelligence--Security measures; Computer security; Cyberterrorism

Keyword

LLMs; Cybersecurity; Large Language Models for Attacks; Large Language Models for Defense; Computer Science; Artificial Intelligance

Discipline

Cybersecurity

Document Type

Theses

Extent

i, 28 leaves

DCMI Type

Text

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by-nc-nd/4.0/

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Cybersecurity Commons

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