正常网络 meaning in English
proper network
Examples
- But the potential for such citizen science is expanding rapidly because of moore ' s law ? the doubling of processor power every 18 months or so ? and a similarly speedy growth of the bandwidth available to ordinary internet users
但是，这种公民科学（或称大众科学）发展迅猛的潜在因素是因为摩尔法则（大约每18个月处理器的能力就会加倍）与正常网络用户所能使用的带宽出现了同样的快速提高。 - It can show significant difference between normal flows and attack flows in the correlation , which offers a new method to analyze the correlation in anomaly detection . the second analysis method is multi - similarity analysis of network charact - eristics
通过主成分宏观分析和微观分析,该方法很好地分析了流量内部微观的行为和关系,很好地区分了正常网络流和异常网络流在相关性上的不同,为异常发现提供了新的思路。 - We do researches on constructing normal model of network traffic , analysizing self - similarity of network traffics - hurst parameter , and its time variable function h ( t ) . experimental analysis confirmed the validity of the novel mechanism , limiting the extent of network traffic in time and detecting the ddos attack through measuring the change of h parameter brought by the attacks . moreover we use database to refine the ddos attack
主要成果为： ( 1 )对网络流量的自相似性? hurst参数、 hurst参数的时变函数h ( t )进行分析，建立正常网络流量模型，比传统的特征匹配更准确描述了网络流量的特性； ( 2 )通过实验验证了，基于正常网络流量模型，对网络流量进行实时限幅，由自相似性的变化来预测ddos攻击方法的正确性； ( 3 )对于不同的攻击方式，我们使用不同的方法进行检测，并用数据库对流经的包头信息进行统计分析，来对攻击定位。 - By adopting the real - time rescaled range ( rrs ) algorithm developed from the rs method , we do the simulation work using fractional gaussian noise ( fgn ) and real network traffic data collected from lan and wan . it shows the method we bring up can differentiate normal network traffic and ddos attack traffic effectively and precisely in most situation , and has provided a new way to detect and prevent ddos attack duly and precisely
通过基于rs算法改进的实时hurst系数估计算法rrs ，采用分形高斯噪声和局域网、广域网真实业务数据进行了仿真实验，结果表明本文所提出的方法可以在绝大多数情况下准确高效地区分正常网络业务和包含了ddos攻击的数据业务，从而为及时、准确地判断和制止大规模ddos攻击的发生提供了新的手段。 - 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。