TCP有限状态机和协议解析在伪警报去除中的应用

面对入侵检测系统(IDS)产生的海量警报,提出了一种基于协议解析和传输控制协议(TCP)有限状态机的伪警报去除方法。对于无连接的请求/应答协议,同时分析请求数据包的攻击特征和应答数据包的返回状态码来去除伪警报;对于TCP,在协议分析的基础上建立TCP数据包的有限状态机的模型,通过判断系列数据包是否为同一TCP连接、是否包含攻击序列来去除伪警报。在DARPA2000的数据集上的实验结果表明,此方法的误警率平均降低了59.47%,对TCP和请求/应答协议的警报的识别率达到76.67%。该方法简单又有效,依赖IDS的攻击特征库,可以插件的形式在线实现。     

对入侵检测警报关联分析的研究与实践

该文从网络入侵检测系统(NIDS)的工作原理、配置策略和警报格式三方面对其重复警报信息量大、误报多的原因进行了详细分析,指出了因此带来的危害。提出利用对警报信息的关联分析方法来调整IDS的配置策略和确定攻击行为,并结合分析的结论和漏洞扫描的结果对网络配置状况进行了重新评估,指出网络中存在的问题,使网络安全管理员及时解决问题,加固系统,提高了网络入侵检测系统的准确性、实用性。     

Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network

In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of records. This paper proposes a novel framework of network security Intrusion Detection System (IDS) using Modified Frequent Pattern (MFP-Tree) via K-means algorithm. The accuracy rate of Modified Frequent Pattern Tree (MFPT)-K means method in finding the various attacks are Normal 94.89%, for DoS based attack 98.34%, for User to Root (U2R) attacks got 96.73%, Remote to Local (R2L) got 95.89% and Probe attack got 92.67% and is optimal when it is compared with other existing algorithms of K-Means and APRIORI.     

An Integrated Intrusion Detection System for Cluster-based Wireless Sensor Networks

A Wireless Sensor Network (WSN) consists of many low-cost, small devices. Usually, as they are deployed to an open and unprotected region, they are vulnerable to various types of attacks. In this research, a mechanism of Intrusion Detection System (IDS) created in a Cluster-based Wireless Sensor Network (CWSN) is proposed. The proposed IDS is an Integrated Intrusion Detection System (IIDS). It can provide the system to resist intrusions, and process in real-time by analyzing the attacks. The IIDS includes three individual IDSs: Intelligent Hybrid Intrusion Detection System (IHIDS), Hybrid Intrusion Detection System (HIDS) and misuse Intrusion Detection System. These are designed for the sink, cluster head and sensor node according to different capabilities and the probabilities of attacks these suffer from. The proposed IIDS consists of an anomaly and a misuse detection module. The goal is to raise the detection rate and lower the false positive rate through misuse detection and anomaly detection. Finally, a decision-making module is used to integrate the detected results and report the types of attacks.     

攻击案例综合学习系统研究

随着入侵检测系统在安全领域的广泛应用，入侵报警学习和分析已经成为一个研究热点。针对目前入侵报警泛滥和知识贫乏等问题，设计了一个完整的攻击案例学习系统框架。该学习系统分为两个阶段：入侵报警精简和典型攻击案例挖掘。前者利用改进的密度聚类方法实现相似报警聚合以及报警聚类的自动精简表示，后者利用序列模式挖掘方法挖掘频繁入侵事件序列。进一步提出一种基于入侵执行顺序约束关系的攻击案例评估算法实现典型攻击案例的自动筛选。最后，利用真实入侵报警数据测试了该攻击案例学习系统，结果表明该系统能够实现高效报警精简和典型攻击案例的准确学习。     

报警信息聚合研究

入侵检测系统的诸多不完善的因素制约了入侵检测的发展,入侵检测一直也成为人们研究的一个重点,而报警信息聚合可以有效地减少报警数量,提高网络预警能力,对入侵检测系统有着十分重大的意义.首先将报警分成四大类,再判定不同类别中报警信息的关系,进行聚合,最后根据不同的属性找出各报警信息的关联关系.     

一种基于多因素的告警关联方法

入侵检测系统作为保护网络安全的重要工具已被广泛使用,其通常产生大量冗余度高、误报率高的告警。告警关联分析通过对底层告警进行综合分析与处理,揭示出其中包含的多步攻击行为。许多告警关联方法通过在历史告警中挖掘频繁模式来构建攻击场景,方法容易受冗余告警、误报影响,挖掘出的多步攻击链在某些情况下不能反映出真实的多步攻击行为。为此,提出一种基于多因素的多步攻击关联方法。通过聚合原始告警以得到超级告警,降低冗余告警带来的影响;将超级告警构造成超级告警时间关系图,同时结合超级告警间的多因素关联度评价函数从时间关系图中挖掘出多步攻击场景。实验结果表明,该方法能克服冗余告警及大部分误报带来的负面影响、有效地挖掘出多步攻击链。     

基于报警序列的入侵场景自动构建

传统的入侵检测系统(IDS)由于其规则的抽象程度较低,导致一次攻击行为会产生大量重复和相关报警.研究表明,入侵场景可提供较高层次的抽象来表示攻击过程,但是已有研究方法均无法在线生成入侵场景.提出一种自动构建入侵场景的方法,将原始报警按照(源,目标)IP对和优先级分类成不同超报警序列集合,从中挖掘频繁闭序列作为入侵场景.在Darpa数据集上的实验表明,该方法可以满足在线运行,并可有效发现攻击过程.     

多步攻击告警关联模型构建与实现

为精简入侵检测系统产生的大量报警信息和分析攻击者的目的和动机,提出了新的报警信息关联模型。该模型通过事件关联把具有相似关系的报警信息关联后存储为元报警,然后根据报警类型知识库转换为超报警,最后根据超报警之间的因果关系进行攻击关联,构建出攻击关联图。实验表明,该模型提高了报警处理效率,对识别攻击意图和提高报警准确性有较好的效果。     

A cooperative agent-based model for active security systems

This paper presents a multi-agent model for implementing active security concepts. In this model, a group of agents can carry out their tasks cooperatively in order to achieve an ultimate security goal. Thus a low-level module of the proposed model reads the values of interesting data items of the relevant current network events and passes them to a relational database. Comparing these measurements against predefined values in an intruder signature database may point to a particular attack.The proposed model consists of two parts. (1) A multiagent Intrusion Detection System (MIDS) for detecting attacks. (2) An Active Security Mechanism (ASM) for taking active, network-wide, response against attackers. The proposed approach provides a customizable host environment built from various systems software components to allow an optimal match between the intrusion circumstances and the underlying security architecture. Thus, different frameworks can support alternative responses of existing security services. In addition, the ASM can take rapid response against attacks by making use of sensible sharing of attack intelligence. System agents communicate with each other on different hosts using an agent communication language through a message router.     

入侵检测报警聚合与关联系统设计与实现

入侵检测系统的大部分报警事件之间都存在某种联系。通过对这些报警的聚合与关联能够消除或减少重复报警，降低误报率及发现高层多步攻击策略。论文设计并实现了一种报警聚合与关联系统，系统主要包括报警聚合、报警校验、多步攻击报警关联和报告分析与规则控制等部分。实验证明：该系统能够减少报警数量，并能识别攻击意图，达到预警的目的。     

Tracing DDoS Floods: An Automated Approach

We propose a Controller-Agent model that would greatly minimize distributed denial-of-service (DDoS) attacks on the Internet. We introduce a new packet marking technique and agent design that enables us to identify the approximate source of attack (nearest router) with a single packet even in the case of attacks with spoofed source addresses. Our model is invoked only during attack times, and is able to process the victims traffic separately without disturbing other traffic, it is also able to establish different attack signatures for different attacking sources and can prevent the attack traffic at the nearest router to the attacking system. It is simple in its implementation, it has fast response for any changes in attack traffic pattern, and can be incrementally deployed. Hence we believe that the model proposed in this paper seems to be a promising approach to prevent distributed denial-of-service attacks.     

IDS alerts correlation using grammar-based approach

Intrusion Detection System (IDS) is a security technology that attempts to identify intrusions. Defending against multi-step intrusions which prepare for each other is a challenging task. In this paper, we propose a novel approach to alert post-processing and correlation, the Alerts Parser. Different from most other alert correlation methods, our approach treats the alerts as tokens and uses modified version of the LR parser to generate parse trees representing the scenarii in the alerts. An Attribute Context-Free Grammar (ACF-grammar) is used for representing the multi-step attacks. Attack scenarii information and prerequisites/consequences knowledge are included together in the ACF-grammar enhancing the correlation results. The modified LR parser depends on these ACF-grammars to generate parse trees. The experiments were performed on two different sets of network traffic traces, using different open-source and commercial IDS sensors. The discovered scenarii are represented by Correlation Graphs (CGs). The experimental results show that Alerts Parser can work in parallel, effectively correlate related alerts with low false correlation rate, uncover the attack strategies, and generate concise CGs.     

安全事件关联分析引擎的研究与设计

入侵检测系统是动态安全防御里的重要环节，现有的入侵检测系统（IDS）存在一个致命的缺陷：误报率高居不下，IDS无法展现事件之间的逻辑关系，结果用户很难了解事件背后隐藏的攻击策略或逻辑步骤。为了解决IDS存在的上述问题，在深入分析入侵技术的基础上提出了基于入侵序列的启发式关联方法，设计并实现了一个事件关联分析引擎，最后验证了有效性。     

基于IDMEF和分类的报警聚合

如何聚合来自不同IDS的报警以减少重复报警是分布式IDS研究的重要问题。设计了一种入侵检测消息交换格式(IDMEF)报警消息格式规范,通过对IDMEF数据模型中的Alert类扩展而成,可统一描述不同IDS上报的报警信息。为有效聚合IDMEF报警,对基于分类和相似度的原始报警聚合算法进行了改进,并在Snort平台上实现了报警聚合模块原型和IDMEF报警生成模块原型。在DARPA99数据集上的实验结果证明了该方案的有效性。     

Measuring IDS-estimated attack impacts for rational incident response: A decision theoretic approach

Intrusion detection system (IDS) plays a vital role in defending our cyberspace against attacks. Either misuse-based IDS or anomaly-based IDS, or their combinations, however, can only partially reflect the true system state due to excessive false alerts, low detection rate, and inaccurate incident diagnosis. An automated response component built upon IDS therefore must consider the stale and imperfect picture inferred from them and takes action accordingly.This article presents an approach for measuring attack impact with the evidence of IDS alerts, with the objective to suggest rational response by cost-benefit analysis. More specifically, based on a very realistic assumption that a system evolves as a Markov decision process conditioned upon the current system state, imperfect observation, and action, we use partially observable Markov decision process to model the efficacy of IDS as providing a probabilistic assessment of the state of system assets, and to maximize a reward signal (defined as a function of both cost and benefit) by taking appropriate actions in response to the estimated system states in terms of desirable security properties. The ultimate goal is to move the system to more secure states with respect to pre-specified security metrics, and assist system administrators to identify the best tradeoff between the cost and benefit of security policies. We finally use a benchmark data set to practically illustrate the application of our methodology and conduct a proof-of-concept validation on its feasibility and efficiency.     

基于软件定义网络的反嗅探攻击方法

网络嗅探攻击中,攻击者从网络节点或链路捕获和分析网络通信数据、监视网络状态、窃取用户名和密码等敏感信息。在攻击发生时,攻击者通常处于静默状态,传统的网络防护手段如防火墙、入侵检测系统（IDS）或入侵防御系统（IPS）很难发现并有效抵御攻击。从网络结构入手,提出基于软件定义网络（SDN）的动态路径跳变（DPH）通信机制,依据空间和时间约束条件,动态改变通信节点之间的路径,宏观上将通信流量相对均匀地分布在多条传输链路中,增加网络嗅探攻击中获取完整数据的难度。实验仿真结果说明,在一定的网络规模下,动态路径跳变能够在不明显降低网络传输性能的条件下有效防御嗅探攻击。     

入侵诱骗、入侵检测、入侵响应三位一体的网络安全新机制

介绍了Honeypot和IDS各自的特点,提出了入侵响应系统IRS(Intrusion Response System)的概念.三者协作工作构成了网络安全新机制.     

分层协作入侵检测系统研究

互联网在给广大互联网用户提供方便的同时也更加方便了黑客在不同地点、不同时刻发起对远程网络或主机的攻击。针对这些分布式攻击模式，该文提出并论述了一个基于Agent的分布式入侵检测系统的框架及其实现。引入这种分层协作IDS的主要目的是为了克服单一的主机入侵检测系统以及网络入侵检测系统的某些缺陷。在分布式网络环境中，不同的系统主体在各自安全域中执行彼此的独立安全策略；同时，这些系统主体通过相互协作构成上一级安全域。系统框架参考目前流行的通用入侵检测框架CIDF构建，通过经过扩展的CISL实现不同组件间的通讯及协作。     

基于成本评估模型的入侵响应系统研究

入侵检测系统可以检测已发生的入侵行为并发出警告。自动入侵响应系统是入侵检测系统的扩展，它可以对检测到的攻击行为自动进行响应，因此对保护网络安全起重要的作用，而各种成本因素对其性能的影响很大。该文给出了自动入侵响应系统的构架，并介绍了一种基于成本评估模型的自动人侵响应系统：描述了其理论基础，分析了各种成本的计算方法及攻击行为分类对成本的影响，总结出成本模型公式；详细描述了创建该模型的方法，包括资产评估和机器学习等；使用仿真技术模拟攻击和响应，给出了实验结果，结果表明使用该模型能极大地降低响应成本；对该模型进行了一些改进以使其可以扩展到有效防御复杂攻击；指出了今后的研究方向。