网络蠕虫传播模型的分析与仿真研究

研究网络安全问题,网络蠕虫是当前网络安全的重要威胁。网络蠕虫传播途径多样化、隐蔽性强、感染速度快等特点。蠕虫模型以简单传染病模型进行传播,无法准确描述网络蠕虫复杂变化特点,网络蠕虫检测正确率比较低。为了提高网络蠕虫检测正确率,提出一种改进的网络蠕虫传播模型。在网络蠕虫传播模型引入动态隔离策略,有效切断网络蠕虫传播途径,采用自适应的动态感染率和恢复率,降低网络蠕虫造成的不利影响。仿真结果表明,相对于经典网络蠕虫传播模型,改进模型有效地加低了网络蠕虫的传播速度,提高网络蠕虫检测正确率和整个网络安全性,为网络蠕虫传播研究提供重要指导。     

基于拓扑结构的蠕虫防御策略仿真分析

提出了基于拓扑结构控制的蠕虫防御策略,并通过构建仿真模型对其进行了仿真验证分析.首先对蠕虫传播所依赖的拓扑结构的主要形式进行了分析,提出了相应的生成算法,并对算法的有效性进行了验证;随后提出了三种拓扑结构控制策略仿真模型;最后分别对这三种策略在不同拓扑结构下的蠕虫传播控制性能进行了仿真实验.实验结果证明:通过适当地控制拓扑结构,可以有效地遏制拓扑相关蠕虫传播.     

Modeling and Automated Containment of Worms

Self-propagating codes, called worms, such as Code Red, Nimda, and Slammer, have drawn significant attention due to their enormously adverse impact on the Internet. Thus, there is great interest in the research community in modeling the spread of worms and in providing adequate defense mechanisms against them. In this paper, we present a (stochastic) branching process model for characterizing the propagation of Internet worms. The model is developed for uniform scanning worms and then extended to preference scanning worms. This model leads to the development of an automatic worm containment strategy that prevents the spread of a worm beyond its early stage. Specifically, for uniform scanning worms, we are able to 1) provide a precise condition that determines whether the worm spread will eventually stop and 2) obtain the distribution of the total number of hosts that the worm infects. We then extend our results to contain preference scanning worms. Our strategy is based on limiting the number of scans to dark-address space. The limiting value is determined by our analysis. Our automatic worm containment schemes effectively contain both uniform scanning worms and local preference scanning worms, and it is validated through simulations and real trace data to be nonintrusive. We also show that our worm strategy, when used with traditional firewalls, can be deployed incrementally to provide worm containment for the local network and benefit the Internet.     

Contagion蠕虫传播仿真分析

Contagion 蠕虫利用正常业务流量进行传播,不会引起网络流量异常,具有较高的隐蔽性,逐渐成为网络安全的一个重要潜在威胁.为了能够了解Contagion蠕虫传播特性,需要构建一个合适的仿真模型.已有的仿真模型主要面向主动蠕虫,无法对Contagion蠕虫传播所依赖的业务流量进行动态模拟.因此,提出了一个适用于Contagion蠕虫仿真的Web和P2P业务流量动态仿真模型,并通过选择性抽象,克服了数据包级蠕虫仿真的规模限制瓶颈,在通用网络仿真平台上,实现了一个完整的Contagion蠕虫仿真系统.利用该系统,对Contagion蠕虫传播特性进行了仿真分析.结果显示:该仿真系统能够有效地用于Contagion蠕虫传播分析.     

结构化对等网中的P2P蠕虫传播模型研究

基于结构化对等网路由表构造方法,抽象出描述P2P节点空间结构特征的命题并加以证明,将命题结论引入蠕虫传播规律的推导过程,使其转化成新问题并加以解决.建立了P2P蠕虫在三种典型结构化对等网中的传播模型,给出刻画P2P蠕虫传播能力的函数,并揭示了覆盖网拓扑对蠕虫传播的负面影响.所有模型都通过了仿真实验的验证.     

A spatial stochastic model for worm propagation: scale effects

Realistic models for worm propagation in the Internet have become one of the major topics in the academic literature concerning network security. In this paper, we propose an evolution equation for worm propagation in a very small number of Internet hosts, hereinafter called a subnet and introduce a generalization of the classical epidemic model by including a second order spatial term which models subnet interactions. The corresponding gradient coefficient is a measure of the characteristic scale of interactions and as a result a novel scale approach for understanding the evolution of worm population in different scales, is considered. Results concerning random scan strategies and local preference scan worms are presented. A comparison of the proposed model with simulation results is also presented. Based on our model, more efficient monitoring strategies could be deployed.     

邮件蠕虫传播与防御的分析研究*

邮件蠕虫利用e-mail在具有power-law结构特点的网络中进行传播,使得传统的蠕虫防御策略失效。结合power-law网络拓扑结构的特点,引入节点免疫和邮件服务器参与两种防御策略,分别对重复感染与非重复感染两种类型的邮件蠕虫传播进行了实验仿真。结果表明,节点的优先免疫类型、免疫起始时间、邮件服务器参与防御时间及蠕虫邮件识别正确率都与邮件蠕虫的传播有着紧密联系。     

多蠕虫传播模型分析

网络蠕虫之间存在着复杂的交互关系,它们对蠕虫的传播、演化等动力学行为有着重要的影响,刻画这些关系有助于找到更好的控制和预防策略。然而,现有模型大多是基于单蠕虫的传播模型。在此,给出一个两类蠕虫的交互模型,重点研究了一类合作型蠕虫的流行对其他蠕虫的影响。运用动力学分析方法,得到了模型的平衡态及其稳定性条件,并仿真验证了理论结果。理论分析与仿真结果均表明,合作型蠕虫不仅能降低其他蠕虫的传播阈值,而且能加快它们的传播速度,同时,在稳定性条件的指导下采用补丁技术可以抑制合作型蠕虫的传播。     

一种新的网络拓扑建模方法

网络拓扑结构能够很好地解决服从某种规律的网络传播行为问题,所以针对不同的预测和改善网络性能的目的,建立合适的网络拓扑模型是非常重要的。从复杂网络拓扑建模的角度出发,综合考虑了节点和链接的加入与消亡、节点的孤立、网络内新增的内部连接以及局域网内部的偏好连接等因素,提出了一个新的网络拓扑建模的方法NBSFN（New Base Scale Free Network）。运用Java和Matlab工具对结果进行了仿真研究,发现仿真结果能够很好地刻画出无标度、小世界等诸多特性。     

网络蠕虫灰传播模型GEM

网络蠕虫传播模型是研究、分析网络蠕虫传播机制、行为特性的重要方法、手段。传统网络蠕虫传播模型都是基于大数定律思想,该类方法在描述蠕虫传播的潜伏期及衰退期时存在一定缺陷,并且完全忽略蠕虫传播过程中涉及到的不确定随机因素。针对传统模型在描述蠕虫传播过程中的上述不足,本文运用灰色理论,依据灰色建模所需历史数据少,不考虑分布规律、变化趋势的特点,提出了一种网络蠕虫的灰传播模型GEM。经模拟仿真分析,验证了该模型的有效性。     

Characterizing and defending against divide-conquer-scanning worms

Internet worms are a significant security threat. Divide-conquer scanning is a simple yet effective technique that can potentially be exploited for future Internet epidemics. Therefore, it is imperative that defenders understand the characteristics of divide-conquer-scanning worms and study the effective countermeasures. In this work, we first examine the divide-conquer-scanning worm and its potential to spread faster and stealthier than a traditional random-scanning worm. We then characterize the relationship between the propagation speed of divide-conquer-scanning worms and the distribution of vulnerable hosts through mathematical analysis and simulations. Specifically, we find that if vulnerable hosts follow a non-uniform distribution such as the Witty-worm victim distribution, divide-conquer scanning can spread a worm much faster than random scanning. We also empirically study the effect of important parameters on the spread of divide-conquer-scanning worms and a worm variant that can potentially enhance the infection ability at the late stage of worm propagation. Furthermore, to counteract such attacks, we discuss the weaknesses of divide-conquer scanning and study two defense mechanisms: infected-host removal and active honeynets. We find that although the infected-host removal strategy can greatly reduce the number of final infected hosts, active honeynets (especially uniformly distributed active honeynets) are more practical and effective to defend against divide-conquer-scanning worms.     

WSS:一个基于NS2的蠕虫模拟系统

网络蠕虫严重威胁着互联网的安全，然而由于其爆发所具有的突然性和大规模性，使得蠕虫研究面临巨大挑战,本文介绍了一个基于NS2的蠕虫模拟系统-WSS,该系统的建立主要分为三部分：首先通过处理BGP路由表信息来获取模拟中用到的Internet抽象网络，然后以传染病学模型为基础对蠕虫传播进行建模，最后将两者在NS2中相结合实现对蠕虫传播的模拟．实验证明，WSS能够在实验室环境中获取同实际蠕虫爆发时类似的统计数据，在理解蠕虫的宏观行为、预测蠕虫的流量、传播速度及危害等方面有着广泛的应用前景．     

复杂网络上具有多感染阶段的传染病传播模型

针对传染病传播模型缺乏多感染阶段的不足,结合SIR和SEIR两种传播模型的特性,提出了一种改进的具有多感染阶段的SIR传染病传播模型(即SInR模型)。该模型充分考虑了不同感染阶段的非均匀感染力对不同网络结构上传染病传播及传播阈值的影响;同时引入相对感染力及传播时间尺度的概念,从网络结构、网络规模及相对感染力方面进行了仿真研究。仿真中无标度网络采用BA模型的生成算法,而小世界网络采用WS模型的生成算法。由仿真可知,感染节点在整个感染过程中大致服从泊松分布,因此在SInR模型下无标度网络的传播速度更快,范围更广;相对感染力对于传染病的大规模爆发存在着一个阈值,当感染力大于阈值时传染病才能大范围地爆发传播,而小于阈值时传染病只会局域小范围传播直至消失,无标度网络的感染力阈值为0.2,小世界网络的感染力阈值为0.24;随着网络规模的增大,传播时间尺度也在增大,相应的传播速度就会降低。仿真结果表明:该模型下无标度网络传染病传播速度更快且影响范围更大;无标度网络的相对传染力的传播阈值小于小世界网络,设置合理阈值有利于降低传染病的传播影响力。     

Treating scalability and modelling human countermeasures against local preference worms via gradient models

A network worm is a specific type of malicious software that self propagates by exploiting application vulnerabilities in network-connected systems. Worm propagation models are mathematical models that attempt to capture the propagation dynamics of scanning worms as a means to understand their behaviour. It turns out that the emerged scalability in worm propagation plays an important role in order to describe the propagation in a realistic way. On the other hand human-based countermeasures also drastically affect the propagation in time and space. This work elaborates on a recent propagation model (Avlonitis et al. in J Comput Virol 3, 87–92, 2007) that makes use of Partial Differential Equations in order to treat correctly scalability and non-uniform behaviour (e.g., local preference worms). The aforementioned gradient model is extended in order to take into account human-based countermeasures that influence the propagation of local-preference worms in the Internet. Certain aspects of scalability emerged in random and local preference strategies are also discussed by means of random field considerations. As a result the size of a critical network that needs to be studied in order to describe the global propagation of a scanning worm is estimated. Finally, we present simulation results that validate the proposed analytical results and demonstrate the higher propagation rate of local preference worms compared with random scanning worms.     

Internet蠕虫传播模型研究

本文就Internet蠕虫的传播模型进行了研究,分析了各种传播模型的特点和适用环境,在此基础上结合良性蠕虫的特点提出了良性蠕虫对抗恶性蠕虫的传播模型。经过比较和分析,理论上证明了蠕虫对抗蠕虫传播模型,有效地补充和改进了传统的Internet蠕虫传播模型,使其更符合Internet蠕虫传播的实际,为进一步研究蠕虫的检测与预防提供了有力的研究方法。与现有模型相比,其降低了对抗蠕虫给网络造成的冲击、可控,并降低了模型的复杂度。     

主动良性蠕虫和混合良性蠕虫的建模与分析

自从1988年Morris蠕虫爆发以来,网络蠕虫就在不断地威胁着网络的安全.传统防范措施已不再适用于蠕虫的防治,使用良性蠕虫来对抗蠕虫正成为一种新的应急响应技术.良性蠕虫的思想就是将恶意的蠕虫转化成良性的蠕虫,而且该良性蠕虫还可以运用相同的感染机制免疫主机.这种方法可以主动地防御恶意蠕虫并且在没有传统的蠕虫防御框架下仍具有潜在的部署能力.首先,分别将主动良性蠕虫和混合良性蠕虫划分成3个子类;然后,基于两因素模型分别对主动良性蠕虫和混合良性蠕虫的3个子类进行建模,推导了在有延迟以及无延迟的情况下6类良性蠕虫的传播模型;最后,通过仿真实验验证了传播模型.更进一步,基于仿真结果讨论了每种良性蠕虫抑制恶意蠕虫的效果,并且得到如下结论:在相同的感染条件下,复合型的混合良性蠕虫抑制蠕虫传播的效果最好.     

蠕虫预警技术研究与进展

当前网络蠕虫对Internet构成重要威胁,如何防范蠕虫已经成为网络安全的重要课题。由于蠕虫传播速度快、规模大,因此必须在蠕虫传播初期就能发现并对其采取相应措施进行隔离。全面分析了蠕虫预警方面的最新研究进展,包括路由器级的蠕虫检测、基于行为的蠕虫检测、蠕虫特征的自动提取,并对蠕虫的特点进行了总结,最后对未来蠕虫检测的可能方向进行了展望。     

Modeling and analysis of passive worm propagation in the P2P file-sharing network

A number of worms, named P2P (peer-to-peer) passive worms, have recently surfaced, which propagate in P2P file-sharing networks and have posed heavy threats to these networks. In contrast to the majority of Internet worms, it is by exploiting users’ legitimate activities instead of vulnerabilities of networks in which P2P passive worms propagate. This feature evidently slows down their propagation, which results in them not attracting an adequate amount of attention in literature. Meanwhile, this feature visibly increases the difficulty of detecting them, which makes it very possible for them to become epidemic. In this paper, we propose an analytical model for P2P passive worm propagation by adopting epidemiological approaches so as to identify their behaviors and predict the tendency of their propagation accurately. Compared with a few existing models, dynamic characteristics of P2P networks are taken into account. Based on this proposed model, the sufficient condition for the global stability of the worm free equilibrium is derived by applying epidemiological theories. Large scale simulation experiments have validated both the proposed model and the condition.     

基于良性益虫的对等网络蠕虫防御技术

对等网络蠕虫利用对等网络的固有特征(如本地路由表、应用层路由等),不仅复制快,而且提供了更好的隐蔽性和传播性,因而其危害大,防御困难。从分析互联网蠕虫及其传播机制入手,对对等网络上的蠕虫(即P2P蠕虫)及其特殊性进行了综合分析。在此基础之上,提出了基于良性益虫的被动激活主动传播防御策略(PAIFDP),并对该策略的技术原理和响应防御系统的功能模块等进行了详细设计。以Peersim仿真平台为基础,对各种不同网络参数下的防御效果和资源消耗情况进行了实验分析。结果表明,基于良性益虫的P2P蠕虫防御技术具有收敛时间快、网络资源消耗少、适应性强等特点。     

DAW: A Distributed Antiworm System

A worm automatically replicates itself across networks and may infect millions of servers in a short period of time. It is conceivable that the cyberterrorists may use a widespread worm to cause major disruption to the Internet economy. Much recent research concentrates on propagation models and early warning, but the defense against worms is largely an open problem. We propose a distributed antiworm architecture (DAW) that automatically slows down or even halts the worm propagation within an Internet service provider (ISP) network. New defense techniques are developed based on the behavioral difference between normal hosts and worm-infected hosts. Particularly, a worm-infected host has a much higher connection-failure rate when it randomly scans the Internet. This property allows DAW to set the worms apart from the normal hosts. We propose a temporal rate-limit algorithm and a spatial rate-limit algorithm, which makes the speed of worm propagation configurable by the parameters of the defense system. The effectiveness of the new techniques is evaluated analytically and by simulations.