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在入侵检测的过程模型中,基于一阶马尔可夫过程模型的检测方法需要存储的数据量较小,而且比较稳定,不会随着程序或训练数据的变化而发生较大变化。这种基于数据挖掘的检测方法分别在数据存储和检测准确度方面具有一定的优势。
In the intrusion detection process model, the detection method based on the first-order Markov process model needs to store a small amount of data and is relatively stable, and does not change greatly with changes in the program or training data. This data mining-based detection method has certain advantages in terms of data storage and detection accuracy respectively.