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：
暂无
中图分类号：
学科分类号：
摘要：
75
引用
收藏
页码：2266 / 2279
相关论文
共 50 条
  • [21] Large language models (LLMs) as agents for augmented democracy
    Gudino, Jairo F.
    Grandi, Umberto
    Hidalgo, Cesar
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2024, 382 (2285):
  • [22] Are Large Language Models (LLMs) Ready for Agricultural Applications?
    Shende, Ketan
    Resource: Engineering and Technology for Sustainable World, 2025, 32 (01): : 28 - 30
  • [23] Biomedical knowledge graph-optimized prompt generation for large language models
    Soman, Karthik
    Rose, Peter W.
    Morris, John H.
    Akbas, Rabia E.
    Smith, Brett
    Peetoom, Braian
    Villouta-Reyes, Catalina
    Cerono, Gabriel
    Shi, Yongmei
    Rizk-Jackson, Angela
    Israni, Sharat
    Nelson, Charlotte A.
    Huang, Sui
    Baranzini, Sergio E.
    BIOINFORMATICS, 2024, 40 (09)
  • [24] Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints
    Lu, Albert
    Zhang, Hongxin
    Zhang, Yanzhe
    Wang, Xuezhi
    Yang, Diyi
    17TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EACL 2023, 2023, : 1982 - 2008
  • [25] Benchmarking Causal Study to Interpret Large Language Models for Source Code
    Rodriguez-Cardenas, Daniel
    Palacio, David N.
    Khati, Dipin
    Burke, Henry
    Poshyvanyk, Denys
    2023 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION, ICSME, 2023, : 329 - 334
  • [26] Evaluating Source Code Quality with Large Language Models: a comparative study
    da Silva Simões, Igor Regis
    Venson, Elaine
    arXiv,
  • [27] Mapping Source Code to Software Architecture by Leveraging Large Language Models
    Johansson, Nils
    Caporuscio, Mauro
    Olsson, Tobias
    SOFTWARE ARCHITECTURE, ECSA 2024 TRACKS AND WORKSHOPS, 2024, 14937 : 133 - 149
  • [28] Requirements Verification Through the Analysis of Source Code by Large Language Models
    Couder, Juan Ortiz
    Gomez, Dawson
    Ochoa, Omar
    SOUTHEASTCON 2024, 2024, : 75 - 80
  • [29] The (ab)use of Open Source Code to Train Large Language Models
    Al-Kaswan, Ali
    Izadi, Maliheh
    2023 IEEE/ACM 2ND INTERNATIONAL WORKSHOP ON NATURAL LANGUAGE-BASED SOFTWARE ENGINEERING, NLBSE, 2023, : 9 - 10
  • [30] CodeT5+: Open Code Large Language Models for Code Understanding and Generation
    Wang, Yue
    Le, Hung
    Gotmare, Akhilesh Deepak
    Bui, Nghi D. Q.
    Li, Junnan
    Hoi, Steven C. H.
    2023 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, EMNLP 2023, 2023, : 1069 - 1088
12345