Weiheng Bai (University of Minnesota), Qiushi Wu (IBM Research), Kefu Wu, Kangjie Lu (University of Minnesota)

In recent years, large language models (LLMs) have been widely used in security-related tasks, such as security bug identification and patch analysis. The effectiveness of LLMs in these tasks is often influenced by the construction of appropriate prompts. Some state-of-the-art research has proposed multiple factors to improve the effectiveness of building prompts. However, the influence of prompt content on the accuracy and efficacy of LLMs in executing security tasks remains underexplored. Addressing this gap, our study conducts a comprehensive experiment, assessing various prompt methodologies in the context of security-related tasks. We employ diverse prompt structures and contents and evaluate their impact on the performance of LLMs in security-related tasks. Our findings suggest that appropriately modifying prompt structures and content can significantly enhance the performance of LLMs in specific security tasks. Conversely, improper prompt methods can markedly reduce LLM effectiveness. This research not only contributes to the understanding of prompt influence on LLMs but also serves as a valuable guide for future studies on prompt optimization for security tasks. Our code and dataset is available at Wayne-Bai/Prompt-Affection.

View More Papers

A Comparison of Three Approaches to Assist Users in...

Michael Clark (Brigham Young University), Scott Ruoti (The University of Tennessee), Michael Mendoza (Imperial College London), Kent Seamons (Brigham Young University)

Read More

AAKA: An Anti-Tracking Cellular Authentication Scheme Leveraging Anonymous Credentials

Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Read More

Commercial Vehicle Electronic Logging Device Security: Unmasking the Risk...

Jake Jepson, Rik Chatterjee, Jeremy Daily (Colorado State University)

Read More

On the Security of Satellite-Based Air Traffic Control

Tobias Lüscher (ETH Zurich), Martin Strohmeier (Cyber-Defence Campus, armasuisse S+T), Vincent Lenders (Cyber-Defence Campus, armasuisse S+T)

Read More