检测代理是该入侵检测系统模型的骨架。
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.
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.
本文提出了一种层次化协作的电气接地论文混合型分布式入侵检测系统模型。
This paper presents a level of collaboration hybrid Distributed Intrusion Detection System Model.
提出了一种基于人体免疫原理的分布式智能入侵检测系统模型和描述了其工作流程。
Finally, a distributed model of intelligent intrusion detection based on the human immune system is raised, and its working process is...
扼要阐述了入侵检测和数据挖掘技术，并建立了采用数据挖掘技术的入侵检测系统模型。
The intrusion detection and data mining technology are elaborated and the intrusion detection system model is established applying data mining technology.
通过对人类免疫系统工作原理的研究，根据其原理、体系结构建立了一个基于免疫原理的网络入侵检测系统模型。
Through the research on the operating principle of human immune system, a NIDS model was given based on its principle and architecture.
提出了基于免疫机制的网络入侵检测系统模型，将CPK可信认证技术应用到该模型中，提出了特征提取分析方法；
Using the similarity of the vaccine injection technology, the CPK attestation algorithm applies into network intrusion detection system based on immune mechanism.
针对现有入侵检测系统的检测时间范围具有一定局限性的缺陷，提出了一种基于两水平算法的入侵检测系统模型(TAIDS)。
To the limitation of current intrusion detection models, an idea of formulating an intrusion detection model system (TAIDS) based on the GMTH Two-level algorithm was presented.
将数据挖掘的聚类分析方法与入侵检测系统相结合，提出了一种入侵检测系统的智能结构模型。
Clustering analytical means of Data Mining is combined with Intrusion Detection System and an intellectual structure pattern used in Intrusion Detection Syst.
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.
为了解决分布式入侵检测系统缺乏动态组织敏捷性的问题，提出了适应数据网格的按需入侵检测模型。
To solve the problem of lacking dynamic organizing agility in distributed intrusion detection systems, an on-demand intrusion detection model adaptive to the Shared data environment was presented.
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.
通过理论研究和仿真试验均表明该模型的健壮性和有效性，它能弥补传统入侵检测系统的一些不足。
Through theoretical study and simulation we show the robustness and effectiveness of the model. It can make up for some shortcomings of the traditional intrusion detection system.
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。
This model uses not only misuse but also anomaly detection technology, and at deployment the host based subsystem cooperates with the network-based subsystem.
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.
在入侵检测系统框架的基础上，通过建立模式匹配的模型特征库和描述系统的流程来说明入侵检测系统的原理。
Through setting up the model characteristic storehouse and describing the systematic procedure, this paper states its principle based on the description of the frame of Intrusion Detection system.
重点讨论了系统结构模型和系统检测入侵的方法及其原理。
The paper discusses the architecture of system in detail, as well as the means of intrusion detection and its workingprinciple.
文章介绍了入侵检测技术的概念、分类和通用入侵检测模型，并分析了入侵检测系统的弱点和局限性。
This paper introduces the concept of intrusion detection technology, classifications and general model, and analyzes the weaknesses and limitations of intrusion detection System.
提出了网络安全中基于多传感器数据融合技术的入侵检测模型，并对入侵检测系统的体系结构进行了详细介绍。
This paper advances an invasion detection model in the network security based on multi-sensor data fusion, and introduces in detail the structure of invasion detection system.
提出了一种基于系统调用序列的入侵检测模型，利用绝对安全环境下的应用程序系统调用序列建立正常行为模式。
In this paper an intrusion detection model based on system call sequences is proposed, and a normal activity mode of the system call sequences in absolute security environment is established.
适应性模型是一种自动建立的基于数据挖掘的入侵检测系统检测模型。
Adaptive model is a detecting model which is automatically built of intrusion detection systems based on data-mining.
模型中所使用的NN系统尚需进一步深入研究，但实验结果表明，该模型是有效的，能够以较低的错误率检测到入侵行为。
The NN system in the model need lucubrate, and the result display, the model is effective, it can detect the intrusion action in lowly mistake rate.
针对传统的入侵检测系统存在的误警率高、存在告警洪流、告警孤立等缺点，引入了数据融合方法，提出了一个分布式入侵检测中的数据融合模型。
Aiming at the problem of traditional intrusion system, such as high false alert rate, alert torrent, alert isolation, a data fusion model in distributed intrusion detection is put forward.
文中提出了一种入侵检测取证系统模型，它考虑把入侵检测和计算机取证技术结合在一起。
The paper proposes the model of IDS and computer forensic system. It connects intrusion detection and computer forensic.
这一模型非常适合用户与入侵检测系统间的信任研究，并根据用户可信模型及入侵检测系统原理提出了用户可信度的计算方法。
This model researches fitly the trust relation between user and IDS, and the computing means of the user trust degree is presented on the basis of the user trust model and the principle of IDS.
本文提出的算法以及入侵系统模型使用入侵检测数据集kddcup99作为测试集验证性能。
The algorithm proposed in this paper realizes the corresponding module and validates the performance in the KDDCUP99 intrusion detection data set.
在利用入侵检测传感器收集相同数据的同时，系统自动建立适应性模型。
While using the same data collected by intrusion detection sensors, adaptive model is automatically built.
在利用入侵检测传感器收集相同数据的同时，系统自动建立适应性模型。
While using the same data collected by intrusion detection sensors, adaptive model is automatically built.
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