A network traffic anomaly detection mechanism is presented based on support vector machine (SVM).
提出了一种基于支持向量机的网络流量异常检测方法。
Anomaly detection based on network traffic model is one of the important research directions in traffic anomaly detection.
基于网络流量模型的异常检测是流量异常检测的一个重要研究方向。
This paper presents and implements a macro-network traffic anomaly detection strategy based on sequential frequent pattern mining.
基于序贯频繁模式挖掘,提出并实现了一种宏观网络流量异常检测的方法。
It is always a difficult problem to erect a model of normal behaviors in the area of network traffic anomaly detection, a method of network intrusion detection.
流量异常检测,作为一种网络入侵检测的方法,存在着如何建立正常行为模型的难题。
Through the comparison of the results from the experiment and wavelet analysis, it shows that network-wide traffic anomaly detection based on subspace method is more simple and effective.
通过实验结果与小波分析结果的对比,证明了基于子空间方法的大规模网络流量异常检测是一种既简单又高效的方法。
Network traffic anomaly refers to the status that traffic behaviors depart from the normal behaviors, which has characteristics of a sudden attack and the unknown threatened characteristics.
网络流量异常是指网络的流量行为偏离其正常行为的情形,具有发作突然、先兆特征未知的特点,有可能在短时间内给网络及其设备带来极大的伤害。
Analysis shows that this model can not only simulate network traffic corresponding to the real network but also detect anomaly traffic to some extent.
分析表明,该模型不仅可以模拟与网络实测数据相似的网络流量,而且具有一定的异常流量发现能力。
A novel online fault detection algorithm based on adaptive auto-regressive (AAR) model is proposed focusing on the anomaly detection of network traffic.
通过研究网络流量异常检测,提出一种新的基于自适应自回归(aar)模型的在线故障检测算法。
Network traffic is broken down into different frequency, and anomaly change of network traffic is detected through the high-frequency power analysis, that is the change of wavelet variance.
将网络流量分解到不同的频段,根据高频段频谱能量,即小波方差的变化对网络流量异常进行检测。
As a result, anomaly detectors tested against simulated data and found effective may prove ineffective when deployed in real networks monitoring real traffic, he says.
DeVale说,因此,根据模拟数据测试并且发现有效的异常探测器在部署到真实网络中去监视真实流量的时候也许是没有效的。
Detecting the network traffic burst anomaly is with great meaning to locate the anomaly in time and response subsequently.
及时发现网络流量的突发异常变化对于快速定位异常、采取后续相应措施具有重要意义。
Anomaly detection collects and analyses traffic data from many MAs, then detects the anomaly signature by SS.
异常检测在多个MA上采集并分析流量数据,在统计服务器上检测流量的异常特征。
What's more, writer has validated the real-time and effectiveness of the classification of traffic and anomaly detection methods by experiment.
并通过实验,验证了本文所提出的流量分类与异常流量检测方法的实时性和有效性。
The anomaly detection algorithms of the large scale network(LSN) were required to analysis the vast network traffic of G bit level in real-time and on-the-fly.
随着网络规模和速度的增加,大规模网络异常发现要求检测算法能够在无保留状态或者少保留状态下对G比特级的海量网络业务量数据进行实时在线分析。
And according to Protocol Analysis detection, it can flag the anomaly traffic, and detect some attack variations, and resist attackers' obfuscation attempts.
利用协议分析技术发现网络中的异常报文,标识出未知攻击,发现攻击者使用的躲避技术和变种攻击。
We will address anomaly detection, and once an attack is detected how to divert traffic to a Guard cluster that provides a multi-layer intelligent filtering complex for intelligent attack mitigation.
我们还将讨论非正常的检测,以及一旦检测出攻击,应当如何把数据流转移到保护集群,保护集群可提供多层智能过滤综合应用,智能地缓解攻击。
We will address anomaly detection, and once an attack is detected how to divert traffic to a Guard cluster that provides a multi-layer intelligent filtering complex for intelligent attack mitigation.
我们还将讨论非正常的检测,以及一旦检测出攻击,应当如何把数据流转移到保护集群,保护集群可提供多层智能过滤综合应用,智能地缓解攻击。
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