PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs)

被引：0
|
作者：
Nazzal, Mahmoud [1 ]
Khalil, Issa [2 ]
Khreishah, Abdallah [1 ]
Phan, NhatHai [1 ]
机构：
[1] New Jersey Institute of Technology, Newark,NJ, United States
[2] Qatar Computing Research Institute, Doha, Qatar
来源：
CCS 2024 - Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security |
关键词：
Adversarial networks - Codegeneration - Functionals - Graph generative adversarial network - Language model - Large language model - Optimisations - Secure and functioning code - Security vulnerabilities - Source codes;
D O I：
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学科分类号：
摘要：
75
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页码：2266 / 2279
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