计算机科学 ›› 2010, Vol. 37 ›› Issue (10): 59-62.

• 计算机网络与信息安全 • 上一篇    下一篇

一种基于改进流形学习方法的云计算入侵检测模型

陈丹伟,侯楠,孙国梓   

  1. (南京邮电大学计算机技术研究所 南京210003) (南京邮电大学计算机学院 南京210003)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家十一五科技支撑计划项目(2007BAK34B06) ,国家自然科学基金(60703086),南京邮电大学攀登计划项目(NY208009)资助。

Novel Cloud Computing Intrusion Detection Model Based on Improved Manifold Learning

CHEN Dan-wei,HOU Nan,SUN Guo-zi   

  • Online:2018-12-01 Published:2018-12-01

摘要: 基于互联网的超级计算模式云计算引起了人们极大的关注,也面临着越来越多的安全威胁。主要构建能够适应云计算环境的入侵检测系统框架。将非线性流形学习算法引入本课题提出的模型,作为特征提取模块对云计算环境下采集的网络数据进行预处理;给出经典流形学习算法LLE的改进研究,以提高后续分类性能。实验表明,该算法是可行和高效的。

关键词: 云计算,入侵检测,流形学习

Abstract: The cloud computing technology which is a new Internet based super-computing model has aroused great concern,facing an increasing number of security threats at the same time. This paper built a intrusion detection system framework which is adapt to the cloud computing environment proposed in this paper. The nonlinear manifold learning algorithm was introduced to the model proposed in this thesis to be the core algorithm of the data pre-processing module, and the improved I_I_E algorithm was given in order to improve the classification performance. I}he simulation result shows that the algorithm is effective and efficient.

Key words: Cloud computing, Intrusion detection, Manifold learning

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