无线Mesh网络入侵检测关键技术研究

本文研究了无线Mesh网络的结构和特点,以及入侵检测系统(IDS)在构建安全WMN中不可替代的作用。深入分析了AdHoc网络IDS、跨层和网络故障检测技术特点以及无线Mesh网络自身的安全需求。在此基础上,本文结合网络故障检测与跨层技术提出了一种基于代理的非对称分布式协作IDS结构,对代理模块设计原则进行了详细分析。最后以MAC自私行为攻击为例对该结构进行了模拟。结果显示,该结构能够很好地适应无线Mesh网络。     

基于联动机制的入侵防御系统

当前的IDS入侵检测系统对于较为复杂的攻击缺乏有效的应对和阻断能力，而防火墙则缺乏针对各种攻击的灵活的过滤策略。文章以snort入侵检测系统和iptables防火墙为实例，构架了一个基于联动机制的入侵防御系统。该系统能够使IDS入侵检测系统与防火墙联动运行，利用IDS的入侵检测能力，动态地为防火墙定制针对各种入侵的过滤规则，实现对入侵行为的实时阻断。     

一种基于移动Agent的抗攻击性IDS模型

随着入侵检测系统(Inhusion Detection System——IDS)性能的逐步提高，攻击者往往在入侵目标网络之前攻击IDS，使其丧失保护功能。在当前常用的分布式入侵检测系统的基础上，提出了一种能够对抗拒绝服务(Denial of Service——DoS)攻击的IDS模型，并指出了将当前的分布式IDS转换成此模型的配置方法。     

基于多代理的入侵检测数据收集模型

提出了一种基于多代理(Agent)的入侵检测数据收集模型。该模型建立在基于多代理的系统安全体系结构之上，与系统其他安全机制相结合，根据需要灵活部署代理，利用代理捕捉入侵和可疑事件，同时实现基于主机和基于网络的数据收集，为入侵检测系统(IDS)提供尽可能及时、完整和准确的数据。     

多代理分布式入侵检测系统在校园网中的应用

近年来，入侵检测系统(IDS)作为信息系统安全的重要组成部分，得到了广泛的重视。可以看到，仅仅采用防火墙技术来构造网络的安全体系是远远不够的，很多攻击可以绕过防火墙。入侵检测技术可以在网络系统受到损害前对入侵行为做出拦截和响应。基于代理的分布式入侵检测系统实现了基于主机和基于网络检测的结合，为网络系统提供更好的安全保护。文中针对防火墙技术的不足，在对入侵检测技术及其通用架构做出分析和研究后，设计了一种基于代理的分布式入侵检测系统，并给出了在某校园网中的实现。     

网络入侵检测系统的应用分析

病毒防范系统、防火墙系统、入侵检测系统(IDS)组成了一个完整的企业网络安全体系,其中IDS系统对无法预知的异常入侵具有实时分析、检测和预报的能力。IDS中所采取的入侵检测技术的优劣决定了该系统对入侵检测的有效性和实时性。     

基于信息融合的入侵检测模型与方法

研究了入侵检测系统(IDS)研究现状，针对当前IDS系统误报率高和对时间及空间上分散的协同攻击无法有效检测的缺陷，引入信息融合和多传感器集成的观点，提出了一个多层次的IDS推理框架和原型系统．该原型系统采用贝叶斯网络作为多传感器融合的工具，用目标树的方法来分析协同攻击的攻击企图，并最终量化系统的受威胁程度．相比现有的IDS，该原型的结构更加完整，能够更容易发现协同攻击并有效的降低误报．     

入侵检测系统负载问题的一种解决方案

日益突出的网络安全问题促进了入侵检测系统(IDS)的研究。在高负载的情况下,入侵检测系统会出现来不及分析审计数据的现象,从而可能遗漏恶意数据,产生漏报。这个问题严重地影响了IDS的性能和使用范围。文章详细讨论了目前各种IDS在负载方面解决办法的优缺点。文章综合分析各种因素,把关键资源作为评判系统负载的指标,采取分布式的体系结构、动态划分计算量以及最近最少攻击的过滤策略,提出了一种较全面的负载解决方案。并根据IDS的数据特点讨论了该方案的负载平衡算法。     

IDS测试中复合攻击测试数据的生成

从近几年的趋势来看,蠕虫以及DDOS等复合攻击将成为今后网络入侵的主要表现形式.入侵检测系统对复合攻击的检测能力逐渐成为入侵检测系统(IDS)能力测试中的一个重要方面.当前的测试方法主要采用搜集实际的攻击工具来进行攻击测试数据的生成.该方法受实际攻击形式的限制,所生成的数据集无法完成对IDS复合攻击检测能力的完备测试,并且不支持攻击的形式化描述与自动生成,使得测试数据集的生成效率很低.为此提出采用人工构造的完备入侵场景库来生成攻击流量,并在攻击流量中混合入噪声流量增加测试的准确性和公平性.基于这些改进,设计了一种针对滥用入侵检测系统评估的复合攻击测试数据生成系统,并应用在实际的IDS评估系统中.     

探讨本体工程方法在分布式IDS中的应用

随着网络的大规模应用．变形攻击和协同攻击等复杂攻击方法层出不穷．而传统的单纯基于主机或基于网络的入侵检测系统(IDS)对这种复杂攻击的检测常常是无能为力的。主机的IDS只能监视其所安装了的系统、只能在外部入侵者侵入系统后才能检测到。基于网络的IDS虽然能够对某个网络段进行监视．以及在入侵到达主机前就能检测到．但不能     

基于移动代理、关键主机隐藏技术的IDS体系结构

本文介绍了一种安全灵活的入侵检测系统体系结构，通过运用关键主机隐藏技术，使关键主机对于主动探测，被动监听均不可见，提高了系统自身的安全性，同时，通过引入移动代理，限制入侵检测系统各部分之间的通信等机制，增强本体系结构对于拒绝服务攻击的抵抗力，系统通过使用智能移动代理在网络节点上收集处理信息，提高了入侵检检测系统的灵活性，减少了网络负载。     

一种新的基于协议树的入侵检测系统的设计

基于协议分析的入侵检测系统避免了传统入侵检测系统的计算量大、准确率低的缺陷。在协议分析的基础上,提出了一种基于带权重协议树的入侵检测系统,给出了其设计方案,该方案进一步提高了检测的准确性和效率,并且可以检测变体攻击、拒绝服务攻击等较难检测的攻击。     

MOVIH-IDS: A mobile-visualization hybrid intrusion detection system

A novel hybrid artificial intelligent system for intrusion detection, called MObile-VIsualization Hybrid IDS (MOVIH-IDS), is presented in this study. A hybrid model built by means of a multiagent system that incorporates an unsupervised connectionist intrusion detection system (IDS) has been defined to guaranty an efficient computer network security architecture. This hybrid IDS facilitates the intrusion detection in dynamic networks, in a more flexible and adaptable manner. The proposed improvement of the system in this paper includes deliberative agents characterized by the use of an unsupervised connectionist model to identify intrusions in computer networks. This hybrid IDS has been probed through several real anomalous situations related to the simple network management protocol as it is potentially dangerous. Experimental results probed the successful detection of such attacks through MOVIH-IDS.     

基于Agent的入侵检测系统体系结构

本文对基于Agnet的分布式入侵检测系统体系结构进行了系统的研究。在分析比较相关的系统体系结构所具有的优点和不足的基础上，提出了一种基于移动Agnet的入侵检测系统的体系结构。相关实验结果表明，使用这种体系结构设计出的IDS系统不仅是非常有效的，而且响应时间短，精确度高，误警率低。     

A hybrid intrusion detection system design for computer network security

Intrusions detection systems (IDSs) are systems that try to detect attacks as they occur or after the attacks took place. IDSs collect network traffic information from some point on the network or computer system and then use this information to secure the network. Intrusion detection systems can be misuse-detection or anomaly detection based. Misuse-detection based IDSs can only detect known attacks whereas anomaly detection based IDSs can also detect new attacks by using heuristic methods. In this paper we propose a hybrid IDS by combining the two approaches in one system. The hybrid IDS is obtained by combining packet header anomaly detection (PHAD) and network traffic anomaly detection (NETAD) which are anomaly-based IDSs with the misuse-based IDS Snort which is an open-source project.The hybrid IDS obtained is evaluated using the MIT Lincoln Laboratories network traffic data (IDEVAL) as a testbed. Evaluation compares the number of attacks detected by misuse-based IDS on its own, with the hybrid IDS obtained combining anomaly-based and misuse-based IDSs and shows that the hybrid IDS is a more powerful system.     

基于Snort的入侵检测系统在校园网的应用

面对越来越复杂的互联网络环境,传统安全体系受到严重威胁,入侵检测系统(Intrusion Detection System,IDS)已经成为安全系统中重要的组成部分。该文简要地介绍了入侵检测系统的分类、原理和系统结构。并以著名开源NIDS Snort为例,设计并实现了一个校园网入侵检测系统。     

An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks

In this paper, we propose a novel Intrusion Detection System (IDS) architecture utilizing both anomaly and misuse detection approaches. This hybrid Intrusion Detection System architecture consists of an anomaly detection module, a misuse detection module and a decision support system combining the results of these two detection modules. The proposed anomaly detection module uses a Self-Organizing Map (SOM) structure to model normal behavior. Deviation from the normal behavior is classified as an attack. The proposed misuse detection module uses J.48 decision tree algorithm to classify various types of attacks. The principle interest of this work is to benchmark the performance of the proposed hybrid IDS architecture by using KDD Cup 99 Data Set, the benchmark dataset used by IDS researchers. A rule-based Decision Support System (DSS) is also developed for interpreting the results of both anomaly and misuse detection modules. Simulation results of both anomaly and misuse detection modules based on the KDD 99 Data Set are given. It is observed that the proposed hybrid approach gives better performance over individual approaches.     

Intrusion detection in computer networks by a modular ensemble of one-class classifiers

Since the early days of research on intrusion detection, anomaly-based approaches have been proposed to detect intrusion attempts. Attacks are detected as anomalies when compared to a model of normal (legitimate) events. Anomaly-based approaches typically produce a relatively large number of false alarms compared to signature-based IDS. However, anomaly-based IDS are able to detect never-before-seen attacks. As new types of attacks are generated at an increasing pace and the process of signature generation is slow, it turns out that signature-based IDS can be easily evaded by new attacks. The ability of anomaly-based IDS to detect attacks never observed in the wild has stirred up a renewed interest in anomaly detection. In particular, recent work focused on unsupervised or unlabeled anomaly detection, due to the fact that it is very hard and expensive to obtain a labeled dataset containing only pure normal events.The unlabeled approaches proposed so far for network IDS focused on modeling the normal network traffic considered as a whole. As network traffic related to different protocols or services exhibits different characteristics, this paper proposes an unlabeled Network Anomaly IDS based on a modular Multiple Classifier System (MCS). Each module is designed to model a particular group of similar protocols or network services. The use of a modular MCS allows the designer to choose a different model and decision threshold for different (groups of) network services. This also allows the designer to tune the false alarm rate and detection rate produced by each module to optimize the overall performance of the ensemble. Experimental results on the KDD-Cup 1999 dataset show that the proposed anomaly IDS achieves high attack detection rate and low false alarm rate at the same time.     

隐秘攻击与入侵检测的体系结构

入侵检测系统（IDS）是目前研究的一个热点，IDS从攻吉者的角度来看待系统安全，已经成为安全体系结构中不可缺少的一个环节，但是目前的IDS检测技术还不够成熟，存在一些方法使得攻击者可能绕开IDS的检测，文章探讨了一种所谓的隐秘攻击技术，这种方法用以攻击传统的基于关键字匹配的IDS，然后从如何检测隐秘攻击的角度出发讨论了IDS的安全体系结构。     

基于多代理技术可自检的分布式入侵检测系统模型

通过对现有多代理技术的分布式入侵检测系统的研究,提出了一种基于多代理技术可自检的分布式入侵检测系统模型,并且对该模型的结构,组成和代理的处理流程进行了描述,该模型是一个开放的系统模型,具有很好的可扩展性,易于加入新的入侵检测代理及相应的自检,也易于增加新的入侵检测模式,代理之间的协同采用代理守护进程来实现。