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anomaly detection中文是什么意思

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  • The application of misuse detection technology and anomaly detection technology in sql server are talked about thoroughly in this paper . we show more emphasis on the anomaly detection technology based on data mining
    接下来分析基于误用的和基于异常的数据库入侵检测技术,重点讨论了基于异常的数据挖掘检测技术在入侵检测中的应用。
  • Some new detection methods have been emerging in the past 45 years , developing the models to perform well on misuse detection and anomaly detection , such as artificial immunity method , hereditary algorithm , data mining etc .
    近四五年来又涌现出了一些新的检测方法,它们产生的模型对异常和滥用都适用,如人工免疫方法、遗传算法、数据挖掘等。
  • With the continuous increase of network scale and speed , to design the network traffic burst anomaly detection algorithms which are required to accurately analyze the massive traffic data in real time is really a challenge
    而随着网络规模和速度的不断增加,流量突发异常检测算法需要实时准确地分析处理海量的网络业务量数据,具有很大的挑战性。
  • Secondly , the anomaly detection model based on k - means algorithm and som network is constructed . it can classify the normal and abnormal network data stream so better to detect the unknown attack
    ( 2 )提出了一种k -均值聚类算法和som自组织神经网络算法相结合的异常检测模型,使得系统可以更好的分类正常数据流和异常数据流,以此来防范未知的攻击。
  • The consistently repeated system call sequences in normal process trace were regarded as macros , and then an anomaly detection model based on system call macros markov chain was created
    把正常程序行为产生的系统调用迹中大量有规律的重复出现的系统调用短序列看成一个个独立的基本单位(宏) ,并以宏为基本单位构建一个基于马尔可夫链的异常入侵检测模型。
  • Firstly , describe the process of using classification algorithms to develop misuse detection models ; then , discuss how to construct anomaly detection models using association rule and frequency episode algorithms in detail
    首先,介绍了利用分类算法构造误用检测模型的过程;其次,详细讨论了如何利用数据挖掘中的关联规则和频繁序列建造异常检测模型。
  • This paper focus on anomaly - based network intrusion detection system ( anids ) , which use two methods to design and implement anomaly detection . one is analysis abnormal packet , the other is analysis abnormal network flow
    一个是对异常数据包的检测,另一个是对异常网络流量来进行检测。本论文从这两个方面设计了一个入侵检测系统( anids ) ,并加以实现。
  • Anomaly detection is an effort to recognize unusual behavior through a profile describing normal behavioral patterns . this measure can discriminate the unknown methods of intrusion but the technique is not mature and false alarm ratio is high
    异常检测是通过构造正常的用户轮廓来检测用户的行为,优点是可以检测到未知的入侵行为,但是技术不成熟,误报率高。
  • This model uses not only misuse but also anomaly detection technology , and at deployment the host based subsystem cooperates with the network - based subsystem . in the distributed ids model , modules run concurrently and cooperate with each other
    该系统模型既综合了基于异常行为的入侵检测和基于特征的入侵检测技术,在配置上又采用主机配置和网络配置相互配合的方式。
  • At present , intrusion detection technique is divided into anomaly detection and misuse detection . the measure of misuse detection is if the information to be dealt with matches the rule in the rule library based on known intrusive methods
    目前,入侵检测技术主要分为两种:误用检测和异常检测,误用检测是根据已知的入侵手段建立一个规则库,待检测的信息与库中规则进行匹配达到检测目的。
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Last modified time:Thu, 14 Aug 2025 00:29:56 GMT

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