对人工智能模型对代码生成安全性的影响进行系统的文献审查
Claudia Negri-Ribalta1, Rémi Geraud-Stewart2, Anastasia Sergeeva3
1Security and Trust, University of Luxembourg, Luxembourg, Luxembourg.
Frontiers in big data
|May 28, 2024
概括
人工智能 (AI) 可以在软件中引入安全漏洞. 本文审查了人工智能生成的代码漏洞,并强调了在人工智能辅助开发中需要量身定制的安全措施.
科学领域:
- 计算机科学 计算机科学
- 软件工程 软件工程 软件工程
- 网络安全 网络安全
背景情况:
- 人工智能 (AI) 越来越多地被采用来帮助软件开发,可能提高编码效率.
- 然而,人工智能生成的代码可能包含安全漏洞,这引发了对软件安全的担忧.
研究的目的:
- 系统地审查人工智能对软件安全的影响.
- 识别和系统化与使用人工智能开发安全关键软件相关的风险.
主要方法:
- 对现有的AI和软件安全研究进行系统的文献审查.
- 分析人工智能生成代码中常见的安全漏洞,包括MITRE CWE前25名漏洞.
主要成果:
- 人工智能模型可以产生具有安全漏洞的软件.
- 识别了人工智能生成代码中的常见缺陷以及利用它们的方法.
- 审查了加强人工智能生成代码安全性的现有策略.
结论:
- 人工智能辅助编码带来了重大的安全挑战.
- 迫切需要强有力的安全措施,如代码验证,适应人工智能生成的代码.
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