Improved FastICA algorithm for data optimization processing in intrusion detection

Ye DU; dan ZHANGYa; hong LIMei; wei ZHANGDa

doi:10.11959/j.issn.1000-436x.2016006

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Improved FastICA algorithm for data optimization processing in intrusion detection

Academic paper | 更新时间：2024-06-05

- Improved FastICA algorithm for data optimization processing in intrusion detection
- Journal on Communications Vol. 37, Issue 1, Pages: 42-48(2016)
- 作者机构：
  
  北京交通大学计算机与信息技术学院，北京 100044
- 作者简介：
- 基金信息：
  
  Beijing Higher Education Young Elite Teacher Project(YETP0548)
- DOI：10.11959/j.issn.1000-436x.2016006
  CLC： TP393
- Online First：2016-01，
  
  Published：25 January 2016
- 稿件说明：
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Ye DU, dan ZHANGYa, hong LIMei, et al. Improved FastICA algorithm for data optimization processing in intrusion detection[J]. Journal on Communications, 2016, 37(1): 42-48.
DOI：

Ye DU, dan ZHANGYa, hong LIMei, et al. Improved FastICA algorithm for data optimization processing in intrusion detection[J]. Journal on Communications, 2016, 37(1): 42-48. DOI： 10.11959/j.issn.1000-436x.2016006.

摘要

为更好实现对入侵检测样本数据的优化处理，提出了一种改进的快速独立成分分析(FastICA)算法，采用基于加权相关系数进行白化处理以减少信息损失，并优化牛顿迭代法使其满足三阶收敛。对算法进行了细致描述，分析了算法的时间复杂度。实验结果表明，该方法可有效减少数据信息损失，具有迭代次数少、收敛速度快等优点，可有效提高入侵检测样本数据的优化效率。

Abstract

For the purpose of achieving the better data optimizat sing results in intrusion detection

an improved FastICA algorithm was proposed. The weighted correlation coefficient was adopted in the phase of albinism processing to reduce information loss

and the Newton's iterative method was improved for third-order convergence. The algorithm was introduced concretely

meanwhile the time complexity was analyzed in detail. The experiment shows that the method has the advantages of less times of iteration and fast speed of convergence

which can effectively decrease the losses of data and increase the efficiency of data optimization in in ion detection.

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references

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