使用机器学习进行加密网络流量分析和分类
Ibrahim A Alwhbi1, Cliff C Zou1, Reem N Alharbi1
1Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
机器学习增强了加密流量分析和分类,这对网络安全至关重要. 本调查详细介绍了了解各种网络模式的方法,并确定了未来的研究方向.
科学领域:
- 网络安全 网络安全
- 网络工程 网络工程
- 机器学习 机器学习
背景情况:
- 加密对于数据保密至关重要,但使传统的网络流量检查变得复杂.
- 多样化的网络流量 (物联网,网络,移动) 的增加需要先进的分析和分类方法.
- 对于网络管理员,网络安全专家和政策执行者来说,了解加密流量至关重要.
研究的目的:
- 提供机器学习应用在加密流量分析中的全面调查.
- 详细说明在这个领域使用机器学习的程序和方法.
- 审查最先进的技术,并探索加密流量分类的未来研究途径.
主要方法:
- 关于最近在机器学习驱动的加密流量分析方面的进展的文献综述.
- 详细解释机器学习流程用于流量分析和分类.
- 对当前最先进的技术和方法进行分类和讨论.
主要成果:
- 确定了用于分析和分类加密网络流量的关键机器学习方法.
- 总结了现场使用的当前技术和方法.
- 突出了基于机器学习的加密流量分析的挑战和机会.
结论:
- 机器学习为理解和分类加密流量提供了强大的工具.
- 该调查为当前实践和未来在这个关键的网络安全领域的研究提供了路线图.
- 有效分析加密流量对于维护网络安全和完整至关重要.
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