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中文摘要：
以提高IDS中数据分类效率为目标,分析了IDS中被检测数据的特点,设计了一种适用于IDS中数据分类的数值归约算法（NRAADCI）。该算法一方面用值域来减少特征值数目,另一方面将孤立的点放大为一个区域以预测类似行为。最后以决策树分类算法为例,通过实验验证了该数值归约算法的有效性。实验结果表明,该算法在降低已有分类算法的时间复杂度的同时使分类准确率有所提升。
英文摘要：
In order to improve the efficiency of data classification in IDS, this paper analyzed the specialties of the detected data in IDS, designed a numerosity reduction algorithm adapting to the data classification in IDS, which used range of values to reduce the amount of feature values and expand an isolated point to a region in order to forecast similar behavior. Finally, verified the validity of the designed algorithm by doing experiments with decision tree algorithms . The results of experiments show that the algorithm can reduce the time complexity and increase the classifying accuracy of the existing classification algorithms.
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Design and Realization of Software for Guard Against DDoS Based on Self_similar and Optimization Fil
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