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| 改进模糊聚类算法在入侵检测中的应用 | |
| 引用本文： | 丁守雪. 改进模糊聚类算法在入侵检测中的应用[J]. 科学技术与工程, 2009, 9(22) |
| 作者姓名： | 丁守雪 |
| 作者单位： | 江苏科技大学计算机科学与工程学院,镇江,212003 |
| 摘 要： | 在模糊c均值算法基础上,提出一种将粒子群算法与c均值算法相结合产生基于自适应粒子群优化的模糊聚类算法(APFC).用KDD cup99数据集进行评估模糊c均值算法和APFC算法检测性能.试验结果表明, APFC均值算法能够避免模糊c均值算法固有的缺点,检测率提高和误报率下降,并且有较高的检测性能. |
| 关 键 词： | 入侵检测 自适应粒子群优化算法 模糊聚类 模糊c-均值算法 |
| 收稿时间： | 2009-08-07 |
| 修稿时间： | 2009-08-19 |
Application of improved Fuzzy Clustering Algorithm on Intrusion Detection System |
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| dingshouxue. Application of improved Fuzzy Clustering Algorithm on Intrusion Detection System[J]. Science Technology and Engineering, 2009, 9(22) | |
| Authors: | dingshouxue |
| Abstract: | Based on the fuzzy C- means algorithm, we proposed the APFC algorithm combining the fuzzy C- means with APSO. Then KDD cup99 data set was applied to both algorithms. The experiment indicates that the APFC algorithm can avoid the inherent shortcomings of the fuzzy C- means algorithm, and has higher detection performance with detection rate rising and false alarm rate falling. |
| Keywords: | Intrusion detection Automatic particle swarm optimization fuzzy clustering fuzzy C- means algorithm |
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