这个思想已经被应用于一个基于网络的入侵检测系统。
最后，提出了一种基于混合神经网络的入侵检测系统模型。
Finally, an intrusion detection system model based on hybrid neural network is presented.
基于网络的入侵检测系统根据网络流量、网络数据包和协议分析来检测入侵。
Network-based intrusion detection system is based on network traffic, network protocol analysis and packet data to detect intrusion.
基于网络的入侵检测系统就是要在大量的网络数据中区分出“自我”和“非我”。
Intrusion detection system based on network is differentiate self from nonself among huge network data.
文中归纳了入侵检测系统的结构和类别，并提出了一个基于网络的入侵检测系统的设计思想。
In this paper, conclude the architecture and classifications of IDS. Then proposed an implementation of a NIDS which is developed on the base of Linux operating system.
该文在分析基于主机和基于网络的入侵检测系统的特点的基础上，提出了一种电子商务安全审计系统的设计。
This paper first analyses the characteristic of the host -based and network -based intrusion detection systems, then presents an audit system for electronic commerce system.
本文主要构建了一种基于RBF神经网络的入侵检测系统，给出了基本的设计思想和算法，以及样本数据的收集和预处理方法。
This thesis constructs an IDS based on RBF neural network, which gives the basic thinking of design and the arithmetic, the method of collection and beforehand disposal way of the sample data.
生物免疫系统的自我保护机制对设计新的网络入侵检测系统具有很好的借鉴意义。
The protection mechanism of the natural immune system has brought us inspirations for designing a novel network intrusion detection system.
在系统中，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，在配置上又采用了主机配置和网络配置相互配合的方式。
In the system, apply the Intrusion detection technique of the based on unusual behavior and signature-based, and adopt the way of host and network configuration cooperating each other.
其次，在介绍常用入侵手段和网络入侵检测系统研究现状的基础上，讨论了当前入侵检测技术面临的挑战和发展趋势展望。
Secondly, on the basis of introduction to the normal intrusion methods and state of art of network IDS, contemporary challenges and trends are discussed about IDS.
入侵检测系统是保护网络系统安全的关键技术和重要手段，是网络安全领域的研究热点。
Intrusion detection system is the key technologies to protect network systems security and is important way of network security, being a hot area of research and development.
入侵检测系统是用来检测网络入侵行为的工具。
IDS (intrusion Detection System) is a tool to detect the network intrusion actions.
网络入侵检测系统的设计中，入侵检测引擎的设计是关键。
In the design of the network intrusion system, the design of the intrusion detection engine is the key link.
本文以数据融合技术中的D -S证据理论为基础，将其运用于分布式入侵检测系统中，提出了基于D - S证据理论的网络入侵预警模型。
Based on D-S evidence theory in data fusion technology, this paper applies it to distributed intrusion detection systems and gives a network intrusion early warning model.
然后，概括地介绍了系统的入侵检测技术，其中包括神经网络、专家系统等人工智能技术在计算机系统入侵检测中的应用。
Then, several intrusion detection techniques are presented, in which artificial intelligent techniques such as neural networks and expert systems are included.
为了进一步提高网络入侵检测系统的检测性能，将模糊积分理论和神经网络技术应用到网络入侵检测中，提出了基于模糊积分的多神经网络融合模型MNNF。
The model of Multiple Neural Networks by Fuzzy(MNNF) integral presented in this paper is an effective method to improve the detection performance of network intrusion detection system.
将该算法应用于入侵检测系统的网络行为智能学习，其误报率仅为10%左右。
When applying the algorithm to network behavior intelligent learning of intrusion detection system, the error rate is about 10%.
本文最后介绍了新型网络入侵检测系统的编码工作。
This thesis finally introduces the work of New Type Network Intrusion Detection System 'code.
入侵检测系统对网络资源上的恶意使用行为进行识别，并为对抗入侵提供重要信息。
Intrusion detection system discerns evil intention of network resource, and offers the important information for confronting with the invasion.
第三章介绍了网络协议基础，常见的攻击方法和原理，入侵检测系统的规范和标准。
Chapter three introduced the foundation of protocols, common attack method and principle, the norms and standards of the intrusion detection system.
本文提出了一种基于数据挖掘的网络入侵检测系统模型。
In this paper, a data mining-based network intrusion detection system model is introduced.
本文在基于数据挖掘的网络入侵检测系统框架基础上设计了一个无导师学习的分析器模型。
Based on the framework of network intrusion detection systems based on data mining, this paper devises an analyzer model of unsupervised learning.
该方法能够检测系统级、网络级和用户级的入侵行为，模拟实验表明该方法有很强的检测能力和较好的鲁棒性。
This method can detect intrusion action on system level, network level and user level, simulation experiment indicates the method has very highly detection ability and robust ability.
用于网络入侵检测系统（IDS）的特征（变量）数量太多或太少都会降低IDS识别入侵者的正确率。
Using too many or too too few characters(variable) in Intrusion Detection System(IDS) leads to reduce recognizing correctness of IDS.
作为保护计算机和网络系统的第二道防线，入侵检测系统的应用的越来越广泛。
As the second line of defense for computer and network systems, intrusion detection systems (IDSs) have been deployed increasingly wider.
它将基于网络和基于主机的入侵检测系统有机地结合在一起，提供集成化的检测、报告和响应功能。
It combines the network based IDS and host based IDS into a system, and provides detection, report and response together.
代理体系的引入，将基于主机的入侵检测和基于网络的入侵检测灵活地融为一体，形成一个统一的入侵检测系统。
Due to the agent system, A_DTDS comes into being a uniform intrusion detection system that is competent for the task of host-based and network-based intrusion detection.
本篇论文针对当前网络入侵检测系统(IDS)的检测规则，提出了一个具有弹性的、实时的，能动态调整入侵规则的方案。
This paper is aimed at testing the rules of the current network intrusion detection system (IDS), a flexible, real-time; rules can be dynamically adjusted to the invasion plan.
实验结果表明，改进的模式匹配算法，更适合于网络级入侵检测的实现，减少了系统的丢包率。
Experimental data showed the improved pattern matching algorithm is better adapted to invasion detection on the network level, thus reducing systematical missing package rate.
基于这个思路，我们设计并实现了一个基于神经网络技术的网络入侵检测系统原型。
Based on this idea, we design and develop a Neural Network-Based Network Intrusion Detection System prototype.
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