连接记录 meaning in English
linkage record
Examples
- On the other hand , this system does not analyze the huge daily record and network record completely , but defines the suspicious intrusion mark , and collect corresponding auditing when this kind of mark appears
另一方面，本方案不对庞大的日志信息和网络连接记录进行完全性分析，而是定义可疑的入侵标记，当出现这种标记时才进行相应的审计记录收集。 - Using this method , raw audit data is first preprocessed into records with a set of basic features . data mining algorithms are then applied to compute the frequent patterns from records , whitch are automatically analyzed to generate an additional set of features for intrusion detection purposes
本方法中，首先把原始审计记录处理成包含基本特征的连接记录，然后应用数据挖掘算法计算连接记录中的频繁模式，并从频繁模式中自动生成入侵检测的附加特征。 - In the fourth section of the thesis , the method that constructing statistical features based - on time for connection records and using these features to construct classification models were studied in detail . in order to improve the accuracy of classification model and decrease the rate of false positive , some factors that may have bad influence on accuracy of classification model were analyzed and the method of selecting appropriate set of features was also provided
论文的第四部分，详细研究了使用网络连接记录的基本特征属性构建基于时间的统计特征属性方法，通过选择适当的特征属性集来提高异常检测模型的分类精度，降低误报率；同时分析了影响检测模型分类精度的因素；对不同实验条件下得到的实验结果进行了比较和分析。 - Raw audit data of the system or network is first preprocessed into records with a set of basic features . then the association algorithms and the frequent algorithms are used to compute the frequent patterns from the records , which are the basis for building or selecting system features
系统中各代理相互协作，对系统或者网络的原始审计数据进行预处理生成包含基本特征的连接记录；利用数据挖掘中的关联规则挖掘算法和频繁序列规则挖掘算法，得到系统事件在属性间和时间序列上的频繁模式。 - The results of trial indicate classification models constructed by this set of features can find an obvious threshold to distinguish between a normal network activity and an abnormal one . so the anomaly classification model offered in this thesis has better performance of detection
通过大量的实验，表明应用我们所提出的基于网络连接记录异常检测分类模型的构建方法，能够以较为明显的阈值把正常网络活动与异常网络活动区分开，因此，本文提出的异常检测分类模型具有较好的检测性能。