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

5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

Haohuang Wen (The Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Ashish Gehani (SRI International), Zhiqiang Lin (The Ohio State University)

Read More

Understanding the Implementation and Security Implications of Protective DNS...

Mingxuan Liu (Zhongguancun Laboratory; Tsinghua University), Yiming Zhang (Tsinghua University), Xiang Li (Tsinghua University), Chaoyi Lu (Tsinghua University), Baojun Liu (Tsinghua University), Haixin Duan (Tsinghua University; Zhongguancun Laboratory), Xiaofeng Zheng (Institute for Network Sciences and Cyberspace, Tsinghua University; QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.)

Read More

Secure Control of Connected and Automated Vehicles Using Trust-Aware...

H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson (Boston University), Wei Xiao (Massachusetts Institute of Technology), Christos Cassandras, Wenchao Li (Boston University)

Read More

Threats Against Satellite Ground Infrastructure: A retrospective analysis of...

Jessie Hamill-Stewart (University of Bristol and University of Bath), Awais Rashid (University of Bristol)

Read More