一种基于深度合成的内部入侵检测 (DS-IID) 模型,用于恶意内部人员和人工智能产生的威胁
Hazem M Kotb1, Tarek Gaber2,3, Salem AlJanah4,5
1The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.
Scientific reports
|January 2, 2025
概括
一个新的深度合成内部入侵检测 (DS-IID) 模型通过区分真实和人工智能产生的威胁来准确识别恶意内部人员. 这种先进的网络安全工具实现了高精度,加强了对复杂内部攻击的防御.
科学领域:
- 网络安全 网络安全
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 内幕威胁是一个主要的IT安全风险,由生成人工智能的创造现实的虚假用户配置文件的能力加剧.
- 现有的入侵检测系统难以将人工智能产生的活动与合法用户行为区分开来,从而造成安全漏洞.
研究的目的:
- 引入一种新的深度合成内部入侵检测 (DS-IID) 模型,以加强恶意内部人员的检测.
- 评估生成算法在复制用户配置文件中的有效性,并区分真实和合成异常用户配置文件.
- 提高对AI驱动内部威胁的入侵检测系统的准确性.
主要方法:
- DS-IID模型利用深度功能合成,从事件数据中生成详细的用户配置文件.
- 二元深度学习用于准确识别威胁.
- 随机加权随机抽样用于管理不平衡的数据集.
主要成果:
- 在CERT内部威胁数据集上,DS-IID模型实现了97%的准确性和0.99的AUC.
- 该模型在区分真实和人工智能产生的 (合成) 威胁方面表现出超过99%的准确性.
- 通过监督学习,DS-IID模型有效地检测恶意内部人员.
结论:
- DS-IID模型在检测内部威胁方面取得了重大进展,特别是涉及人工智能生成欺骗的内部威胁.
- 该模型在区分真实和合成威胁方面的高准确性突出显示了其对真实世界网络安全应用的潜力.
- 建议对各种数据集进行进一步评估,以充分评估模型的稳定性.
相关概念视频
01:18Steps in Outbreak Investigation
89
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
89
02:16Stereotype Content Model
13.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.9K
01:20Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences
317
Inductively coupled plasma–mass spectrometry (ICP–MS) is a highly selective and sensitive technique for accurate elemental analysis. Though the analysis of ICP–MS mass spectra is comparatively straightforward, it is affected by spectroscopic and non-spectroscopic interferences. Spectroscopic interferences arise when the plasma contains ionic species with an m/z value the same as the analyte ion. Spectroscopic interference can be categorized as isobaric, polyatomic ions, and...
317