1) Survey of outlier detection technologies
异常检测综述
2) anomaly detection
异常检测
1.
Attribute selection-based and support vector machine for anomaly detection;
基于特征选择和支持向量机的异常检测
2.
Network anomaly detection based on attributes similarity and cloud model;
基于属性相似度云模型的网络异常检测
3.
Unsupervised anomaly detection based on a multi-layer perceptron;
一种基于多层感知机的无监督异常检测方法
3) abnormal detection
异常检测
1.
Research on method of network abnormal detection based on Hurst parameter estimation;
基于Hurst参数评估的网络异常检测方法的研究
2.
Protected scheme for email virus based on abnormal detection
基于异常检测的邮件病毒防治方案
3.
This paper proposes one kind of network intrusion and abnormal detection models on the basis of a network supporting vector machine,which can inspect network intrusion and abnormal detection with the class II categorized ability of support vector machine(SVM).
针对入侵检测系统(IDS)这门新兴的安全技术,提出了一种基于支持向量机的网络入侵异常检测模型,以支持向量机(SVM)的二类分类能力对网络入侵进行异常检测,实验结果与ANN方法结果相比较证明:该方法具有较高的准确性,而且可以大大缩短训练与检测时间。
4) outlier detection
异常检测
1.
Continuous outlier detection over evolving data streams.;
演化数据流上的连续异常检测
2.
Efficient outlier detection method based on Voronoi diagram;
一种基于Voronoi图的高效异常检测方法
3.
Application of structural damage diagnosis using density-based outlier detection;
模式密度方法在结构异常检测中的应用研究
5) anomaly detecting
异常检测
1.
Design and implementation of anomaly detecting engine for inter-domain routing system;
域间路由系统异常检测引擎的设计与实现
2.
In order to reduce the impact of sampled traffic on network anomaly detecting,a novel method with variable sampling rates in traffic sampling is proposed.
为了减小抽样数据对网络异常检测的影响,提出了一种新的可变抽样率的网络流量抽样方法。
6) abnormity detection
异常检测
1.
Design of the abnormity detection model based on data mining technology;
基于数据挖掘技术的异常检测模型设计
2.
Then,abnormity detection based on data flow is introduced and three stages of detecting are given.
首先分析了造成网络拥塞现象的深层次原因及恶意数据流对拥塞的影响,进而阐述了基于数据流的网络异常检测对控制网络拥塞的作用,并给出了进行网络异常检测的三个基本步骤。
补充资料：异常
①不同于平常：情况异常｜异常的交往。②副词。非常；特别：异常激动｜异常兴奋｜照顾异常周到。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条