大规模预训练模型在信息安全领域的应用研究
Research on the application of large scale pre training models in the field of information security
田雄军 1崔佳斌 1袁礼 2杨凯锋3
作者信息
- 1. 国家电子计算机质量检验检测中心,北京 100083
- 2. 北京经济管理职业学院,北京 100102
- 3. 中国电子信息产业集团公司第六研究所,北京 102200
- 折叠
摘要
[目的/意义]探讨大规模预训练模型在信息安全领域的应用研究.[方法/过程]阐述大规模预训练模型的基本原理,结合实际分析大规模预训练模型在信息安全中的优势和面临的挑战,由此展现信息安全中运用大规模训练模型在上下文理解语义分析能力、集成多模态数据能力等方面的优势,以及在隐私与安全性、数据偏差和样本不平衡方面存在的问题.[结果/结论]重点针对自然语言处理、网络安全和入侵检测等信息安全任务,探讨了大规模预训练模型的应用实践,为信息安全领域预训练模型的合理、有效的运用,提供一些思路和理论基础,以期通过预训练模型的运用,在一定程度上提高信息安全管理水平.
Abstract
[Purpose/Significance]Explored the application research of large-scale pre training models in the field of information security.[Method/Process]The basic principles of large-scale pre training models were briefly explained,and the advantages and challenges of large-scale pre training models in information security were analyzed in combination with practical situations.From this,the advantages of using large-scale training models in context understanding and semantic analysis,as well as the ability to integrate multimodal data,in terms of privacy and security,were clearly understood in information security Challenges in data bias and sample imbalance.[Results/Conclusion]Focused on information security tasks such as natural language processing,network security,and intrusion detection,the application practice of large-scale pre trained models was explored.This study aims to provide some ideas and theoretical basis for the rational and effective application of pre trained models in the field of information security,with the aim of improving information security management to a certain extent through the application of pre trained models.
关键词
预训练模型/信息安全/自然语言处理/网络安全/应用研究Key words
pre trained model/information security/natural language processing/network security/application research引用本文复制引用
出版年
2024
NETL
NSTL
万方数据