由内部网络误用引起的安全问题已日益成为网络安全管理研究领域中的一个难题。
The security problem resulting from internal computer network misuse is becoming even more difficult in the researching field of network security management.
实验证明，在由若干子网组成的大规模网络中，该方法可以高效地检测出任意一个子网内是否存在网络误用。
Proved by the experiment, put into the large-scale network composed by several subnets, this method can detect the misuse of any subnet with a high efficiency.
实验证明，在由若干子网组成的大规模网络中，该方法可以高效地检测出任意一个子网内是否存在网络误用。
Proved by the experiment, put into the large-scale network composed by several subnets, this method can detect the misuse of any subnet wit...
电子邮件，而不是网络，从应用来看是使用的最多的互联网应用，同时也是被误用最多的。
Email, not the web, is the most-used Internet application by transaction volume. It's also the most misused.
在网络入侵检测算法方面，本文对异常和误用检测算法进行了研究。
On the aspect of network intrusion detection algorithm, the thesis studies the misuse detection algorithm and anomaly detection algorithm.
其中规则库中包含正常行为规则和异常行为规则，使得原型系统在理论上既可实现误用检测也可实现异常检测，并采用关联规则挖掘模块对网络连接数据进行处理。
The rule sets of the system include normal behavior rules and abnormal behavior rules, it make the system can carry out the anomaly detection and misuse detection in theory.
另外，收集一个网络的使用和误用情况也是非常重要的。
Collect an usage of network moreover and misemploy a circumstance is also count for much.
入侵检测技术从原理上分为异常检测和误用检测，从检测内容上分为主机入侵检测和网络入侵检测技术。
On principle, Intrusion detection technology is made up of abnormal detection and musing detection and by the detected content, it includes host detection and network detection.
这些信息可以有助于判断网络的误用、它的性质，它的来源。
This information can, in turn, help to determine network misuse, its nature, and its source.
因此，防范网络犯罪的关键在于防止信息的误用和滥用。
So how to prevent information from misusing and abusing is the focus in fighting against network crimes.
电子邮件，而不是网络，从应用来看是使用的最多的互联网应用，同时也是被误用最多的。
Email, not the web, is the most-used Internet application by volume. It's also the most misused.
在文中，针对误用网络型入侵检测系统建立一个警报过滤机制，该机制找出攻击成功时所需具备的环境条件。
This paper proposes an alarm filtering scheme to improve the efficiency of misuse-type network intrusion detection system.
通过对网络数据包的分析，挖掘出网络系统中频繁发生的行为模式，并运用模式相似度比较对系统的行为进行检测，进而自动建立异常和误用行为的模式库。
By analysis of network traffic (packets), frequent user behavior profiles are mined, and then by comparing the profile similarity, system behavior can be detected in real-time.
通过对网络数据包的分析，挖掘出网络系统中频繁发生的行为模式，并运用模式相似度比较对系统的行为进行检测，进而自动建立异常和误用行为的模式库。
By analysis of network traffic (packets), frequent user behavior profiles are mined, and then by comparing the profile similarity, system behavior can be detected in real-time.
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