覆盖网络中病毒防范策略的研究
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摘要
覆盖网络是构建于其它网络之上的网络,通常由终端结点或用户自主建立连接关系而形成。常见的覆盖网络包括对等网络、社会关系网络等。由于覆盖网络具有灵活的实现架构和按需的路由机制,因此可以方便快捷地用于构建多种不同的应用,其中典型的应用包括对等网络文件共享、流媒体等多媒体应用和社交网络等。
学术界和工业界对覆盖网络的研究和设计都层出不穷,已有的工作大部分着重于应用实现、性能优化和网络演化等方面,而覆盖网络的安全问题并没有被大多数研究所关注。其实,覆盖网络和传统网络一样,存在着恶意结点和恶意行为,诸如病毒、网络蠕虫、分布式拒绝服务攻击、虚假身份之类的攻击行为在覆盖网络同样存在;另一方面,覆盖网络往往由终端结点自主参与拓扑构建和消息路由等网络功能,因此这些攻击甚至会比传统网络中的还要容易实现且危害更大。尽管覆盖网络可以实现令人较为满意的高扩展性、动态适应性、服务可靠性等特征,但是如果没有很好地解决其安全问题,那么即不能给形成一个自我完备的网络架构体系,又不能吸引用户参与到安全需求较高的网络应用中来。因此要考查覆盖网络的安全相关问题,并以最常见和重要的病毒传播问题为主线,提出并研究覆盖网络中病毒防范策略。
由于覆盖网络是重叠于已有网络之上的上层网络,因此在整体架构上存在两方面的特征——已有网络本身的特征和覆盖网络独有的特征。从覆盖网络的角度看,网络由用户、用户所依赖的终端载体(如计算机主机、设备等)和网络连接几个要素组成。这一层病毒防范策略需要解决的问题也就相应地包括防范用户行为相关的病毒传播、防范基于载体活动的病毒传播和防范利用覆盖网络连接路由机制的病毒传播等几个方面。而从底层网络的角度看,仍然需要从疫情前和疫情后两方面来进行防范,对病毒的接触范围和传播速率进行控制。
根据上述思路,提出综合有效防范覆盖网络病毒的体系,概括如下:
第一,提供应用层路由的安全中转机制。病毒可以利用应用层连接信息增加攻击的针对性和命中率,因此在覆盖网络中普遍采取的应用层中转路由层面上提供防范策略可以有效降低病毒的初期爆发速率;
第二,提供用户行为的良性导控。病毒期望加速用户对病毒体(如感染文件)的共享和传播,所以通过良性的资源特征展示与导控,可以相应地遏制这种攻击方式;
第三,提供终端载体活动的准入机制。不同场景中终端载体的角色不同,其活动对病毒传播的作用也不尽相同,有效地保护关键角色的终端载体意味着可以有效地限制病毒;
第四,通过网络隔离策略限制病毒的可接触范围。网络分簇和隔离可以将病毒潜在的破坏范围进行数量级的缩小,即保护了大部分结点,又降低了底层病毒的传播命中率;
第五,通过分布式目标免疫策略恢复感染结点。实现高效的目标免疫,使其具有覆盖网络所需的动态性和分布性,是直接清除病毒的有效措施。
以上前面三点是对覆盖网络特有机制提出的防范策略,后面两点是对底层网络已有机制提出的防范策略。通过有机地将这些措施组合成一个高效、灵活的防范体系,可以在很大程度上预防和限制病毒的产生和扩散。同时,通过病毒防范模型和测量与仿真结果,可以深入理解防范覆盖网络病毒的关键,为科学理解覆盖网络安全问题提供踏实的认知基础,对于维护覆盖网络安全具有重要的理论和实际意义。
An overlay network is a network that is built over another network, which is commonly established by the end hosts or users' making connections autonomally. Typical overlay networks include Peer-to-Peer networks, social networks, etc. As the overlay networks have the characteristics such as flexible architectures and on-demand routing mechanisms, they can conventionally build variety of applications, such as Peer-to-Peer file sharing, media streaming and online social websites.
Although the academic and industrial circles have studied overlay networks extensively, much of the existing work focuses on the application realization, performance improvement, network evolution, etc., while the security issues of overlay networks are not widely concerned. Actually, similar to traditional networks, there are malicious nodes and behaviors in the overlay networks, including virus, worms, Denial of Service attacks, fake identities, etc. From the perspective of the fact that the overlay networks allow end hosts to participate in topology construction and message routing, these security issues are much easier to perform and can lead to worse situations in overlay networks. Even if the overlay network technology can realize relatively satisfying system scalability, dynamic adaptation and service reliability, there will be no self-contained network architecture and it cannot attract users to high security demand applications, if the security issues are not really solved. Therefore, the security related problems are investigated, and taking the most general and important issues - the virus/worm epidemics - as the research objects, defensive strategies are proposed and studied in overlay networks.
Since an overlay networks is in the upper layer which covers an existing network, its architecture consists of two aspects: the original one in the existing network and the emerging one in the overlay network. From the overlay network's perspective, the components include the users, the carriers which the users rely on (e.g., computers and devices), and connections among them. Then to defend these components against the epidemics, corresponding strategies should cover of user behavior related epidemic defense, carrier activity based epidemic defense and overlay network routing mechanism based epidemic defense. While from the existing network's perspective, the epidemics should be still handled both in advance and afterwards, especially on containing the epidemic affect range and propogation rate.
Based on above understandings, a thorough and effective defense framework of overlay network epidemics is summarized as below:
First, to provide a secure relay mechanism for the application level routing. Epidemics can take advantage of application level information to increase the attack hit rate, so providing effective defense on the relay mechanism which is commonly used by overlay networks can reduce the propagation rate in the beginning of an epidemic;
Second, to provide a benign guidance on user behaviors. The epidemics anticipate accelerating the spread of virus entity (e.g., infected files), so by well-designed guidance on user behaviors through resource property presentation, the attack can be correspondingly contained;
Third, to provide the admission mechanism in carrier activities. In different scenarios the carriers play various roles, which act differently on the epidemic propogation, so Securing key roles (carriers) effectively means restricting the epidemic effectively;
Fourth, to limit the attack range of epidemics by the network partition strategy. Network clustering and partition can shrink the potential contact range of the epidemics to several degrees, which both guard a majority of end nodes and slow the hit rate of epidemics in underlying networks;
Fifth, to restore infected nodes by the distributed targeted immunization strategy. Realizing effective targeted immunization and providing it with desired dynamic and distributed adaptation is considered as a powerful solution to clean up the epidemics.
The former three points are from the overlay network's view and the latter two are from the underlying network's view. By integrating these strategies into a highly effective and flexible defensive framework, the epidemics in overlay network can be mostly defended. Besides, by the defensive models and measurement and simulation results, a better understanding of the keys in overlay network epidemic defensive strategies can be obtained, and the foundation of perceiving the security issues in overlay networks can be formed. It is believed this work has significant theoretical and practical meanings for keeping the overlay network in safety.
学术界和工业界对覆盖网络的研究和设计都层出不穷,已有的工作大部分着重于应用实现、性能优化和网络演化等方面,而覆盖网络的安全问题并没有被大多数研究所关注。其实,覆盖网络和传统网络一样,存在着恶意结点和恶意行为,诸如病毒、网络蠕虫、分布式拒绝服务攻击、虚假身份之类的攻击行为在覆盖网络同样存在;另一方面,覆盖网络往往由终端结点自主参与拓扑构建和消息路由等网络功能,因此这些攻击甚至会比传统网络中的还要容易实现且危害更大。尽管覆盖网络可以实现令人较为满意的高扩展性、动态适应性、服务可靠性等特征,但是如果没有很好地解决其安全问题,那么即不能给形成一个自我完备的网络架构体系,又不能吸引用户参与到安全需求较高的网络应用中来。因此要考查覆盖网络的安全相关问题,并以最常见和重要的病毒传播问题为主线,提出并研究覆盖网络中病毒防范策略。
由于覆盖网络是重叠于已有网络之上的上层网络,因此在整体架构上存在两方面的特征——已有网络本身的特征和覆盖网络独有的特征。从覆盖网络的角度看,网络由用户、用户所依赖的终端载体(如计算机主机、设备等)和网络连接几个要素组成。这一层病毒防范策略需要解决的问题也就相应地包括防范用户行为相关的病毒传播、防范基于载体活动的病毒传播和防范利用覆盖网络连接路由机制的病毒传播等几个方面。而从底层网络的角度看,仍然需要从疫情前和疫情后两方面来进行防范,对病毒的接触范围和传播速率进行控制。
根据上述思路,提出综合有效防范覆盖网络病毒的体系,概括如下:
第一,提供应用层路由的安全中转机制。病毒可以利用应用层连接信息增加攻击的针对性和命中率,因此在覆盖网络中普遍采取的应用层中转路由层面上提供防范策略可以有效降低病毒的初期爆发速率;
第二,提供用户行为的良性导控。病毒期望加速用户对病毒体(如感染文件)的共享和传播,所以通过良性的资源特征展示与导控,可以相应地遏制这种攻击方式;
第三,提供终端载体活动的准入机制。不同场景中终端载体的角色不同,其活动对病毒传播的作用也不尽相同,有效地保护关键角色的终端载体意味着可以有效地限制病毒;
第四,通过网络隔离策略限制病毒的可接触范围。网络分簇和隔离可以将病毒潜在的破坏范围进行数量级的缩小,即保护了大部分结点,又降低了底层病毒的传播命中率;
第五,通过分布式目标免疫策略恢复感染结点。实现高效的目标免疫,使其具有覆盖网络所需的动态性和分布性,是直接清除病毒的有效措施。
以上前面三点是对覆盖网络特有机制提出的防范策略,后面两点是对底层网络已有机制提出的防范策略。通过有机地将这些措施组合成一个高效、灵活的防范体系,可以在很大程度上预防和限制病毒的产生和扩散。同时,通过病毒防范模型和测量与仿真结果,可以深入理解防范覆盖网络病毒的关键,为科学理解覆盖网络安全问题提供踏实的认知基础,对于维护覆盖网络安全具有重要的理论和实际意义。
An overlay network is a network that is built over another network, which is commonly established by the end hosts or users' making connections autonomally. Typical overlay networks include Peer-to-Peer networks, social networks, etc. As the overlay networks have the characteristics such as flexible architectures and on-demand routing mechanisms, they can conventionally build variety of applications, such as Peer-to-Peer file sharing, media streaming and online social websites.
Although the academic and industrial circles have studied overlay networks extensively, much of the existing work focuses on the application realization, performance improvement, network evolution, etc., while the security issues of overlay networks are not widely concerned. Actually, similar to traditional networks, there are malicious nodes and behaviors in the overlay networks, including virus, worms, Denial of Service attacks, fake identities, etc. From the perspective of the fact that the overlay networks allow end hosts to participate in topology construction and message routing, these security issues are much easier to perform and can lead to worse situations in overlay networks. Even if the overlay network technology can realize relatively satisfying system scalability, dynamic adaptation and service reliability, there will be no self-contained network architecture and it cannot attract users to high security demand applications, if the security issues are not really solved. Therefore, the security related problems are investigated, and taking the most general and important issues - the virus/worm epidemics - as the research objects, defensive strategies are proposed and studied in overlay networks.
Since an overlay networks is in the upper layer which covers an existing network, its architecture consists of two aspects: the original one in the existing network and the emerging one in the overlay network. From the overlay network's perspective, the components include the users, the carriers which the users rely on (e.g., computers and devices), and connections among them. Then to defend these components against the epidemics, corresponding strategies should cover of user behavior related epidemic defense, carrier activity based epidemic defense and overlay network routing mechanism based epidemic defense. While from the existing network's perspective, the epidemics should be still handled both in advance and afterwards, especially on containing the epidemic affect range and propogation rate.
Based on above understandings, a thorough and effective defense framework of overlay network epidemics is summarized as below:
First, to provide a secure relay mechanism for the application level routing. Epidemics can take advantage of application level information to increase the attack hit rate, so providing effective defense on the relay mechanism which is commonly used by overlay networks can reduce the propagation rate in the beginning of an epidemic;
Second, to provide a benign guidance on user behaviors. The epidemics anticipate accelerating the spread of virus entity (e.g., infected files), so by well-designed guidance on user behaviors through resource property presentation, the attack can be correspondingly contained;
Third, to provide the admission mechanism in carrier activities. In different scenarios the carriers play various roles, which act differently on the epidemic propogation, so Securing key roles (carriers) effectively means restricting the epidemic effectively;
Fourth, to limit the attack range of epidemics by the network partition strategy. Network clustering and partition can shrink the potential contact range of the epidemics to several degrees, which both guard a majority of end nodes and slow the hit rate of epidemics in underlying networks;
Fifth, to restore infected nodes by the distributed targeted immunization strategy. Realizing effective targeted immunization and providing it with desired dynamic and distributed adaptation is considered as a powerful solution to clean up the epidemics.
The former three points are from the overlay network's view and the latter two are from the underlying network's view. By integrating these strategies into a highly effective and flexible defensive framework, the epidemics in overlay network can be mostly defended. Besides, by the defensive models and measurement and simulation results, a better understanding of the keys in overlay network epidemic defensive strategies can be obtained, and the foundation of perceiving the security issues in overlay networks can be formed. It is believed this work has significant theoretical and practical meanings for keeping the overlay network in safety.
引文
[1]S.Banerjee,B.Bhattacharjee,C.Kommareddy.Scalable Application Layer Multicast.in:Proceedings of ACM SIGCOMM,Pittsburgh,PA,ACM Press,Aug.19-23,2002.205-217
[2]周文莉,雷振明.BitTorrent文件共享系统的一种流量模型与文件评估方法.计算机工程,2006,32(13):15-17
[3]I.Stoica,R.Morris,D.Karger,et al.Chord:a Scalable Peer-to-Peer Lookup Service for Internet Applications.in:Proceedings of ACM SIGCOMM,San Diego,CA,ACM Press,Aug.27-31,2001.149-160
[4]刘军,张琳.基于DHT发现端到端多条覆盖网路径的方法.计算机工程与设计,2008,29(16):4197-4199
[5]Y.Kulbak,D.Bickson.The eMule Protocol Specification,eMule Project,2005,http://sourceforge.net
[6]X.Hei,C.Liang,J.Liang,et al.Insights into PPLive:A Measurement Study of a Large Scale P2P IPTV System.in:Proceedings of 15~(th) International World Wide Web Conference(WWW'06),Edinburgh,Scotland,IEEE Press,May 23-26,2006
[7]X.Liao,H.Jin,Y.Liu,et al.Anysee:Peer-to-Peer Live Streaming.in:Proceedings of the 25~(th) IEEE Computer and Communications Societies(INFOCOM'06),Barcelona,Spain,IEEE Press,Apr.23-29,2006.1-10
[8]毛军鹏,崔艳莉,马祥杰,等.Skype网络流量测量及特征发现.计算机工程,2008,34(18):142-144
[9]H.Jin,H.Yao,X.Liao,et al.PKTown:A Peer-to-Peer Middleware to Support IPTV and Multiplayer Online Games.in:Proceedings of the 1~(st) International Conference on Multimedia and Ubiquitous Engineering(MUE),Seoul,Korea,IEEE Press,Apr.26-28,2007
[10]H.Yao,L.Yu,H.Jin,et al.Ripple:Toward a Substrate Middleware for Peer-to-Peer Applications.in:Proceedings of IEEE ICICIC'08,Dalian,China,IEEE Press,Jun.18-20,2008.376-376
[11]Facebook,http://www.facebook.com
[12]MySpace,http://www.myspace.bom
[13]开心网,http://www.kaixin001.com
[14]校内网,http://www.xiaonei.com
[15]P.Gill,M.Arlitt,Z.Li,et al.Youtube Traffic Characterization:a View from the Edge.in:Proceedings of ACM SIGCOMM,Kyoto,Japan,ACM Press,Aug.27-31,2007.15-28
[16]Flickr,http://www.flicker.com
[17]S.Sen,J.Wang.Analyzing Peer-to-Peer Traffic across Large Networks.in:IEEE/ACM Transactions on Networking(TON),Apr.2004,12(2):219-232
[18]N.Channa,S.Li,W.Shi,et al.A CAN-based P2P Infrastructure for Semantic Web Services Publishing and Discovery.in:Proceedings of the 1~(st) IEEE and IFIP International Conference in Central Asia on Internet,Hangzhou,China,Sep.26-29,2005.5-5
[19]B.Y.Zhao,L.Huang,J.Stribling,et al.Tapestry:a Resilient Global-Scale Overlay for Service Eeployment.in:IEEE Journal on Selected Area in Communications,Jan.2004,22(1):41-53
[20]P.Maymounkov,D.Mazieres.Kademlia:A Peer-to-peer Information System Based on the XOR Metric.in:Proceedings of the 1~(st) International Workshop on Peer-to-Peer Systems(IPTPS),Cambridge,MA,USA,Mar.7-8,2002
[21]D.Stutzbach,R.Rejaie.Characterizing the Two-Tier Gnutella Topology.in:Proceedings of International Conference on Measurement and Modeling of Computer Systems(SIGMETRICS),Alberta,Canada,ACM Press,Jun.6-10,2005.402-403
[22]闫清泉,吴刚,奚宏生,等.BitTorrent系统中瞬间拥挤阶段建模与分析.小型微型计算机系统,2008,29(10):1807-1810
[23]W.Yu,S.Chellappan,X.Wang,et al.On Defending Peer-to-Peer System-based Active Worm Attacks.in:Proceedings of IEEE Global Telecommunications Conference(GLOBECOM),St.Louis,USA,IEEE Press,Nov.28-Dec.2,2005.5-5
[24]X.Nie,Y.Wang,J.Jing,et al.Understanding the Impact of Overlay Topologies on Peer-to-Peer Worm Propagation.in:Proceedings of International Conference on Computer Science and Software Engineering(CSSE),Wuhan,China,IEEE Press,Dec.12-14,2008.863-867
[25]J.Liang,R.Kumar,Y.Xi,et al.Pollution in P2P File Sharing Systems.in:Proceedings of the IEEE Computer and Communications Societies(INFOCOM), Miami, USA, IEEE Press, Mar. 13-17,2005. 1174-1185
[26] M. E. J. Newman, S. Forrest and J. Balthrop. Email Networks and the Spread of Computer Viruses. in: Phys. Rev. E, 2002, 66:035101
[27] B. Krishnamurthy, C. Wills. On the Leakage of Personally Identifiable Information Via Online Social Networks. in: Proceedings of the 2~(nd) ACM SIGCOMM Workshop on Online Social Networks (WOSN'09), Barcelona, Spain, ACM Press, Aug. 17, 2009. 7-12
[28] S. Saroiu, P. K. Gummadi, S. D. Gribble. A Measurement Study of Peer-to-Peer File Sharing Systems. in: Proceedings of the 9th Annual Multimedia Computing and Networking Conference (MMCN'02), San Jose, CA, ACM Press, Jan. 2002
[29] Napster, http://www.napster.com
[30] J. Liang, R. Kumar, K. W. Ross. The FastTrack Overlay: a Measurement Study. in: Computer Networks, Elsevier, Apr. 2006, 50(6): 842-858
[31] J. A. Pouwelse, P. Garbacki, D. H. J. Epema, et al. The BitTorrent P2P File-Sharing System: Measurements and Analysis. in: Proceedings of the 4 International Workshop on Peer-to-Peer Systems (IPTPS), Ithaca, USA, Feb. 24-25,2005
[32] P. K. Gummadi, R. J. Dunn, S. Sariou, et al. Measurement, Modeling and nalysis of a Peer-to-Peer File-Sharing Workload. in: Proceedings of ACM Symposium on Operating Systems Principles (SOSP'03), New York, USA. ACM Press, Oct. 19-22, 2003.314-329
[33] W. Tang, Y. Fu, L. Cherkasova, et al. MediSyn: A Synthetic Streaming Media Service Workload Generator. in: Proceedings of the 13~(th) International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV), Monterey, California, USA. ACM Press, Jun. 1-3,2003. 12-21
[34] D. Qiu and R. Srikant. Modeling and Performance Analysis of BitTorrent-like Peer-to-Peer Networks. in: Proceedings of ACM SIGCOMM, Portland, USA, ACM Press, Aug. 30-Sep. 3,2004. 367-378
[35] L. Guo, S. Chen, Z. Xiao, et al. Measurements, Analysis, and Modeling of BitTorrent-like Systems. in: Proceedings of Internet Measurement Conference (IMC'05), Berkeley, USA, ACM Press, Oct. 19-21,2005. 1-14
[36] M. Piatek, T. Isdal, T. Anderson, et al. Do Incentives Build Robustness in BitTorrent? in: Proceedings of the 4~(th) USENIX Symposium on Networked Systems Design and Implementation (NSDI'07), Cambridge, USA, Apr. 11-13,2007
[37] M. Sirivianos, J. H. Park, R. Chen, et al. Free-riding in BitTorrent Networks with the Large View Exploit. in: Proceedings of the 6 International Workshop on Peer-to-Peer Systems (IPTPS'07), Bellevue, WA, Feb. 2007
[38] R. Kumar, D. Yao, A. Bagchi, et al. Fluid Modeling of Pollution Proliferation in P2P Networks. in: Proceedings of ACM SIGMETRICS, Saint-Malo, France, ACM Press, Jun. 26-30, 2006. 335-346
[39] X. Zhang, J. Liu, B. Li, et al. CoolStreaming/DONet: A Data-Driven Overlay Network for Efficient Live Media Streaming. in: Proceedings of the IEEE Computer and Communications Societies (INFOCOM), Miami, USA. IEEE Press, Mar. 13-17, 2005.2102-2111
[40] P. Dhungel, X. Hei, K. W. Ross, et al. The Pollution Attack in P2P Live Video Streaming: Measurement Results and Defenses. in: Proceedings of ACM SIGCOMM Workshop on Peer-to-Peer Streaming and IPTV (P2P-TV), Kyoto, Japan, ACM Press, Aug. 31,2007. 323-328
[41] F. Benevenuto, M. Vasconcelos, J. Almeida, et al. Impact of Peer Incentives on the Dissemination of Polluted Content. in: Proceedings of ACM Symposium on Applied Computing (SAC), Dijon, France, ACM Press, Apr. 23-27,2006. 1875-1879
[42] A. J. Ganesh, A.M. Kermarrec, L. Massoulie. Peer-to-peer Membership Management for Gossip-based Protocols. in: Transactions on Computers, Feb. 2003, 52(2): 139-149
[43] J. Liang, N. Naoumov, K. W. Ross. Efficient Blacklisting and Pollution-level Estimation in P2P File-sharing Systems. in: Proceedings of the Asian Internet Engineering Conference (AINTEC), Bangkok, Thailand, Dec. 13-15,2005
[44] C. K. Wong, S. S. Lam. Digital Signatures for Flows and Multicasts. in: IEEE/ACM Transactions on Networking, Aug. 1999,7(4): 502-513
[45] E. Palomar, J. M. Estevez-Tapiador, J. C. Hernandez-Castro, et al. A Protocol for Secure Content Distribution in Pure P2P Networks. in: Proceedings of the 17~(th) International Conference on Database and Expert Systems Applications (DEXA'06), Krakow, Poland, Sep. 4-8,2006. 712-716
[46] J. Scott. Social Network Analysis: A Handbook. Sage, London, 2nd edition, 2000
[47] H. Ebel, J. Davidsen, S. Bornholdt. Dynamics of Social Networks. in: Complexity, 2002, 8(2):24-27
[48] R. Pastor-Satorras, A. Vespignani. Epidemic Spreading in Scale-Free Networks. in: Physical Review Letters, 2001, 86(14):3200
[49] Rose 病毒解决办灶,http://baike.baidu.com/view/869091.htm
[50] Nimaya Worm, http://it.rising.com.cn/Channels/Service/2006-11/1163505486d3873 4.shtml.
[51] N. Weaver, S. Staniford, V. Paxson. Very Fast Containment of Scanning Worms. in: Proceedings of the 12~(th) USENIX Security Symposium (Security'04), Aug. 9-13, 2004
[52] A. Levi, C. K. Koc. Risks in Email Security. in: Communications of the ACM, , August 2001,44(8): 112-112
[53] K. Takahashi, T. Abe, M. Kawashima. Stopping Junk Email by Using Conditional ID Technology: privango. in: NTT Technical Review, 2005, 3(3):52-56
[54] T. Oda, T. White. Immunity from Spam: an Analysis of an Artificial Immune System for Junk Email Detection. in: Proceedings of the 4~(th) International Conference on Artificial Immune Systems, Banff, Alberta, Canada, Springer, Aug. 14-17, 2005. 276-289
[55] Symantec Security Products, http://www.symantec.com
[56] P. Holme. Efficient Local Strategies for Vaccination and Network Attack. in: Europhys. Lett. 2004, 68:908-914
[57] F. Castaneda, E. C. Sezer and J. Xu. WORM vs. WORM: Preliminary Study of an Active Counter-attack Mechanism. in: Proceedings of ACM Workshop on Rapid Malcode (WORM), Fairfax, USA, ACM Press, Oct. 2004. 83-93
[58] D. Moore, C. Shannon, G. M. Voelker, et al. Internet Quarantine: Requirements for Containing Self-propagating Code. in: Proceedings of the 22~(nd) Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'03), San Francisco, USA, Mar. 2003. 1901-1910
[59] K. G. Anagnostakis, M. B. Greenwald, S. Ioannidis, et al. A Cooperative Immunization System for an Untrusting Internet. in: Proceedings of the 11~(th) IEEE International Conference on Networking (ICON'03), Sydney, Australia IEEE Press, Sep. 28-Oct. 1,2003.403-408
[60] O. Diekmann, J. A. P. Heesterbeek. Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. New York: Wiley, 2000
[61] C. Wong, C. Wang, D. Song, et al. Dynamic Quarantine of Internet Worms. in: Proceedings of the IEEE International Conference on Dependable Systems and Networks (DSN), Palazzo dei Congressi, Florence, Italy, Jun. 28-Jul. 1,2004. 73-82
[62] L. Chen, K. M. Carley. The Impact of Countermeasure Propagation on the Prevalence of Computer Viruses. in: IEEE Transactions on Systems, Man, and Cybernetics,Part B:Cybernetics,Apr.2004,34(2):823-833
[63]Z.Dezso,A.-L.Barabsi.Halting Viruses in Scale-Free Networks.in:Physical Review E,2002,65:055103
[64]R.P.Satorras,A.Vespignani.Immunization of Complex Networks.in:Physical Review E,2002,65:036104
[65]R.Pastor Satorras and A.Vespignani.Epidemics and Immunization in Scale-Free Networks.in:Handbook of Graphs and Networks:From the Genome to the Internet,Wiley-VCH,2003
[66]R.Cohen,S.Havlin,D.Ben-Avraham.Efficient Immunization Strategies for Computer Networks and Populations.in:Physical Review Letters,2003,91(24),247901
[67]金海,廖小飞.P2P技术原理与应用.中兴通讯技术,2007,13(6):1-5
[68]X.Huang,Y.Li,R.Yang,et al.Enhancing Attack Survivability of Gnutella-like P2P Networks by Targeted Immunization Scheme.in:Proceedings of the 6~(th) International Conference on Parallel and Distributed Computing,Applications and Technologies (PDCAT'05),Dalian,China,IEEE Press,Dec.5-8,2005.503-506
[69]M.M.Williamson.Throttling Viruses:Restricting Propagation to Defeat Mobile Malicious Code.in:Proceedings of ACSAC'02,Las Vegas,USA,IEEE Press,Dec.9-13,2002.61-68
[70]A.Ganesh,D.Gunawardena,P.Key,et al.Efficient Quarantining of Scanning Worms:Optimal Detection and Coordination.in:Proceedings of the 25~(th) Annual Joint Conference of the 25~(th) Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM),Barcelona,Spain,IEEE Press,April 2006.1-13
[71]L.Xie and S.Zhu.A Feasibility Study on Defending against Ultra-fast Topological Worms.in:Proceedings of the 7~(th) International Conference on Peer-to-Peer Computing(P2P'07),Galway,Ireland,IEEE Press,Sep.2-5,2007.61-70
[72]F.Freitas,R.Rodrigues,C.Ribeiro,et al.Verme:Worm Containment in Peer-to-Peer Overlays.in:Proceedings of the 6th International Workshop on Peer-to-Peer Systems(IPTPS'07),Bellevue,WA,USA,Feb.26-27,2007
[73]S.Yang,H.Jin,B.Li,et al.The Content Pollution in Peer-to-Peer Live Streaming Systems:Analysis and Implications.in:Proceedings of the 37th International Conference on Parallel Processing(ICPP),Portland,Oregon,USA.IEEE Press,Sep.8-12,2008.652-659
[74] S. Yang, H. Jin, B. Li, et al. A Modeling Framework of Content Pollution in Peer-to-Peer Video Streaming Systems. in: Computer Networks, Elsevier, 2009, doi:10.1016/j.comnet.2009.06.004
[75] N. Christin, A. S. Weigend, J. Chuang. Content Availability, Pollution and Poisoning in File Sharing Peer-to-Peer Networks. in: Proceedings of the 6~(th) ACM Conference on Electronic Commerce (EC'05), Vancouver, British Columbia, Canada, ACM Press, Jun. 2005. 68-77
[76] B. Li, S.-S. Xie, G. Y. Keung, et al. Inside the New Coolstreaming: Principles and Measurements. in: IEEE Journal on Selected Areas in Communications, Special Issue on Advances in Peer-to-Peer Streaming System, Dec. 2007,25(9): 1-13
[77] C. Zhang, H. Jin, D. Deng, et al. Anysee: Multicast-based Peer-to-Peer Media Streaming Service System. in: Proceedings of Asia-Pacific Conference on Communications (APCC), Perth, Australia, Oct. 3-5,2005. 274-278
[78] S. Yang, H. Jin, X, Tu. TOBAB: A Trend-Oriented Bandwidth Adaptive Buffering in Peer-to-Peer Streaming System. in: Proceedings of the 3~(rd) International Conference on Autonomic and Trusted Computing (ATC'06), Wuhan and Three Gorges, China, Springer, Sep. 3-6,2006. 113-122
[79] M. Garetto, D. R. Figueiredo, R. Gaeta, et al. A Modeling Framework to Understand the Tussle between ISPs and Peer-to-Peer File Sharing Users. in: Performance Evaluation, Springer, Oct. 2007, 64(9-12):819-837
[80] Y.-H. Chu, S. G. Rao and H. Zhang. A Case for End System Multicast. in: Proceedings of International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), Santa Clara, CA, ACM Press, Jun. 18-21, 2000. 1-12
[81] D. Tran, K. Hua and T. Do. ZIGZAG: An Efficient Peer-to-Peer Scheme for Media Streaming. in: Proceedings of the 22~(nd) Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'03), San Francisco, USA, IEEE Press, Mar. 30-Apr. 3,2003. 1283-1292
[82] PeerCast P2P Radio, http://www.peercast.org
[83] F. Wang, Y. Xiong, J. Liu. mTreebone: A Hybrid Tree/Mesh Overlay for Application-Layer Live Video Multicast. in: Proceedings of the 27~(th) International Conference on Distributed Computing Systems (ICDCS'07), Lisboa, Portugal, IEEE Press, Jun. 25-27,2006.49-49
[84] F. Wang, J. Liu, Y. Xiong. Stable Peers: Existence, Importance, and Application in Peer-to-Peer Live Video Streaming.in:Proceedings of the 26~(th) Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM),Phoenix,AL,USA.IEEE Press,Apr.13-18,2008.1364-1372
[85]Q.Huang,H.Jin,X.Liao.P2P Live Streaming with Tree-Mesh Hybrid Overlay.in:Proceedings of the 37~(th) International Conference on Parallel Processing(ICPP'07)Workshop on HOT-MP2P,Xi'an,China,IEEE Press,Sep.10-14,2007.55-55
[86]S.Saroiu,K.P.Gummadi,S.D.Gribble.Measuring and Analyzing the Characteristics of Napster and Gnutella Hosts.in:Multimedia System,Aug.2003,9(2):170-184
[87]S.Yang,H.Jin,B.Li,et al.Measuring Web Feature Impacts in BitTorrent-like Systems.in:Proceedings of The Fifth International ICST Conference on Heterogeneous Networking for Quality,Reliability,Security and Robustness (QShine'08),Hong Kong,China,Jul.28-31,2008
[88]S.Yang,H.Jin,B.Li,et al.Measuring Web Feature Impacts in Peer-to-Peer File Sharing Systems.in:Computer Communications,Elsevier,2009,doi:10.1016/j.comcom.2009.02.011
[89]B.Cohen.Incentives Build Robustness in BitTorrent.in:Proceedings of P2P Economics Workshop'03,Berkeley,USA,Jun.2003
[90]S.Yang,H.Jin,X.Liao,et al.Modeling Modern Social-Network-Based Epidemics:A Case Study of Rose.in:Proceedings of the 5~(th) International Conference on Autonomic and Trusted Computing(ATC'08),Oslo,Norway,Springer,Jun.23-25,2008.302-315
[91]A.Grabowskia,R.A.Kosifiski.The SIS Model of Epidemic Spreading in a Hierarchical Social Network.in:Acta.Phys.Polon.B,2005,36:1579-1593
[92]Z.Liu and B.Hu.Epidemic Spreading in Community Networks.in:Europhysics Letters,2005,72(2):315
[93]R.Pearlman.An Overview of PKI Trust Models.in:IEEE Network,1999,13(6):38-43
[94]S.Yang,H.Jin,B.Li,et al.Worm Containment in Peer-to-Peer Networks.in:Proceedings of International Conference on Scalable Computing and Communications(ScalCom),Dalian,China,IEEE Press,Sep.25-27,2009.to appear
[95]韩宗芬,陶智飞,杨思睿,等.一种基于自治域的协同入侵检测与防御机制.华 中科技大学学报(自然科学版),2006,34(12):53-55
[96]D.Moore,C.Shannon.Code-Red:a Case Study on the Spread and Victims of an Internet Worm.in:Proceedings of the 2~(nd) ACM SIGCOMM Workshop on Internet Measurement(IMW'02),Marseille,France,ACM Press,Nov.6-8,2002.273-284
[97]D.Moore,V.Paxson,S.Savage,et al.Inside the Slammer Worm.in:IEEE Security and Privacy Magazine,Jul.2003,1(4):33-39
[98]M.Crotti,M.Dusi,F.Gringoli,et al.Traffic Classification through Simple Statistical Fingerprinting.in:ACM SIGCOMM Computer Communication Review,,Jan.2007,37(1):7-16
[99]S.Yang,H.Jin,X.Liao,et al.OnRipple:A Distributed Overlay Framework for Targeted Immunization in Large-Scale Networks.in:Proceedings of the 8~(th) ACIS International Conference on Software Engineering,Artificial Intelligence,Networking and Parallel/Distributed Computing(SNPD'07),Qingdao,China,IEEE Press,Jul.30-Aug.1,2007.911-916
[100]M.E.J.Newman.The Structure and Function of Complex Networks.in:SIAM Review,2003,45(2):167-256
[101]A.Montresor,M.Jelasity,O.Babaoglu.Robust Aggregation Protocols for Large-Scale Overlay Networks.in:Technical Report,University of Bologna,Italy,Dec.2003,UBLCS-2003-16
[102]W.Aiello,F.Chung,L.Lu.A Random Graph Model for Massive Graphs.in:Proceedings of the 32~(nd) Annual ACM Symposium on Theory of Computing,Association of Computing Machinery,New York,USA,ACM Press,2000.171-180
[103]B.Wong,A.Slivkins,E.G.Sirer.Meridian:A Lightweight Network Location Service without Virtual Coordinates.in:Proceedings of ACM SIGCOMM,Philadelphia,USA,ACM Press,Aug.22-26,2005.85-96
[2]周文莉,雷振明.BitTorrent文件共享系统的一种流量模型与文件评估方法.计算机工程,2006,32(13):15-17
[3]I.Stoica,R.Morris,D.Karger,et al.Chord:a Scalable Peer-to-Peer Lookup Service for Internet Applications.in:Proceedings of ACM SIGCOMM,San Diego,CA,ACM Press,Aug.27-31,2001.149-160
[4]刘军,张琳.基于DHT发现端到端多条覆盖网路径的方法.计算机工程与设计,2008,29(16):4197-4199
[5]Y.Kulbak,D.Bickson.The eMule Protocol Specification,eMule Project,2005,http://sourceforge.net
[6]X.Hei,C.Liang,J.Liang,et al.Insights into PPLive:A Measurement Study of a Large Scale P2P IPTV System.in:Proceedings of 15~(th) International World Wide Web Conference(WWW'06),Edinburgh,Scotland,IEEE Press,May 23-26,2006
[7]X.Liao,H.Jin,Y.Liu,et al.Anysee:Peer-to-Peer Live Streaming.in:Proceedings of the 25~(th) IEEE Computer and Communications Societies(INFOCOM'06),Barcelona,Spain,IEEE Press,Apr.23-29,2006.1-10
[8]毛军鹏,崔艳莉,马祥杰,等.Skype网络流量测量及特征发现.计算机工程,2008,34(18):142-144
[9]H.Jin,H.Yao,X.Liao,et al.PKTown:A Peer-to-Peer Middleware to Support IPTV and Multiplayer Online Games.in:Proceedings of the 1~(st) International Conference on Multimedia and Ubiquitous Engineering(MUE),Seoul,Korea,IEEE Press,Apr.26-28,2007
[10]H.Yao,L.Yu,H.Jin,et al.Ripple:Toward a Substrate Middleware for Peer-to-Peer Applications.in:Proceedings of IEEE ICICIC'08,Dalian,China,IEEE Press,Jun.18-20,2008.376-376
[11]Facebook,http://www.facebook.com
[12]MySpace,http://www.myspace.bom
[13]开心网,http://www.kaixin001.com
[14]校内网,http://www.xiaonei.com
[15]P.Gill,M.Arlitt,Z.Li,et al.Youtube Traffic Characterization:a View from the Edge.in:Proceedings of ACM SIGCOMM,Kyoto,Japan,ACM Press,Aug.27-31,2007.15-28
[16]Flickr,http://www.flicker.com
[17]S.Sen,J.Wang.Analyzing Peer-to-Peer Traffic across Large Networks.in:IEEE/ACM Transactions on Networking(TON),Apr.2004,12(2):219-232
[18]N.Channa,S.Li,W.Shi,et al.A CAN-based P2P Infrastructure for Semantic Web Services Publishing and Discovery.in:Proceedings of the 1~(st) IEEE and IFIP International Conference in Central Asia on Internet,Hangzhou,China,Sep.26-29,2005.5-5
[19]B.Y.Zhao,L.Huang,J.Stribling,et al.Tapestry:a Resilient Global-Scale Overlay for Service Eeployment.in:IEEE Journal on Selected Area in Communications,Jan.2004,22(1):41-53
[20]P.Maymounkov,D.Mazieres.Kademlia:A Peer-to-peer Information System Based on the XOR Metric.in:Proceedings of the 1~(st) International Workshop on Peer-to-Peer Systems(IPTPS),Cambridge,MA,USA,Mar.7-8,2002
[21]D.Stutzbach,R.Rejaie.Characterizing the Two-Tier Gnutella Topology.in:Proceedings of International Conference on Measurement and Modeling of Computer Systems(SIGMETRICS),Alberta,Canada,ACM Press,Jun.6-10,2005.402-403
[22]闫清泉,吴刚,奚宏生,等.BitTorrent系统中瞬间拥挤阶段建模与分析.小型微型计算机系统,2008,29(10):1807-1810
[23]W.Yu,S.Chellappan,X.Wang,et al.On Defending Peer-to-Peer System-based Active Worm Attacks.in:Proceedings of IEEE Global Telecommunications Conference(GLOBECOM),St.Louis,USA,IEEE Press,Nov.28-Dec.2,2005.5-5
[24]X.Nie,Y.Wang,J.Jing,et al.Understanding the Impact of Overlay Topologies on Peer-to-Peer Worm Propagation.in:Proceedings of International Conference on Computer Science and Software Engineering(CSSE),Wuhan,China,IEEE Press,Dec.12-14,2008.863-867
[25]J.Liang,R.Kumar,Y.Xi,et al.Pollution in P2P File Sharing Systems.in:Proceedings of the IEEE Computer and Communications Societies(INFOCOM), Miami, USA, IEEE Press, Mar. 13-17,2005. 1174-1185
[26] M. E. J. Newman, S. Forrest and J. Balthrop. Email Networks and the Spread of Computer Viruses. in: Phys. Rev. E, 2002, 66:035101
[27] B. Krishnamurthy, C. Wills. On the Leakage of Personally Identifiable Information Via Online Social Networks. in: Proceedings of the 2~(nd) ACM SIGCOMM Workshop on Online Social Networks (WOSN'09), Barcelona, Spain, ACM Press, Aug. 17, 2009. 7-12
[28] S. Saroiu, P. K. Gummadi, S. D. Gribble. A Measurement Study of Peer-to-Peer File Sharing Systems. in: Proceedings of the 9th Annual Multimedia Computing and Networking Conference (MMCN'02), San Jose, CA, ACM Press, Jan. 2002
[29] Napster, http://www.napster.com
[30] J. Liang, R. Kumar, K. W. Ross. The FastTrack Overlay: a Measurement Study. in: Computer Networks, Elsevier, Apr. 2006, 50(6): 842-858
[31] J. A. Pouwelse, P. Garbacki, D. H. J. Epema, et al. The BitTorrent P2P File-Sharing System: Measurements and Analysis. in: Proceedings of the 4 International Workshop on Peer-to-Peer Systems (IPTPS), Ithaca, USA, Feb. 24-25,2005
[32] P. K. Gummadi, R. J. Dunn, S. Sariou, et al. Measurement, Modeling and nalysis of a Peer-to-Peer File-Sharing Workload. in: Proceedings of ACM Symposium on Operating Systems Principles (SOSP'03), New York, USA. ACM Press, Oct. 19-22, 2003.314-329
[33] W. Tang, Y. Fu, L. Cherkasova, et al. MediSyn: A Synthetic Streaming Media Service Workload Generator. in: Proceedings of the 13~(th) International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV), Monterey, California, USA. ACM Press, Jun. 1-3,2003. 12-21
[34] D. Qiu and R. Srikant. Modeling and Performance Analysis of BitTorrent-like Peer-to-Peer Networks. in: Proceedings of ACM SIGCOMM, Portland, USA, ACM Press, Aug. 30-Sep. 3,2004. 367-378
[35] L. Guo, S. Chen, Z. Xiao, et al. Measurements, Analysis, and Modeling of BitTorrent-like Systems. in: Proceedings of Internet Measurement Conference (IMC'05), Berkeley, USA, ACM Press, Oct. 19-21,2005. 1-14
[36] M. Piatek, T. Isdal, T. Anderson, et al. Do Incentives Build Robustness in BitTorrent? in: Proceedings of the 4~(th) USENIX Symposium on Networked Systems Design and Implementation (NSDI'07), Cambridge, USA, Apr. 11-13,2007
[37] M. Sirivianos, J. H. Park, R. Chen, et al. Free-riding in BitTorrent Networks with the Large View Exploit. in: Proceedings of the 6 International Workshop on Peer-to-Peer Systems (IPTPS'07), Bellevue, WA, Feb. 2007
[38] R. Kumar, D. Yao, A. Bagchi, et al. Fluid Modeling of Pollution Proliferation in P2P Networks. in: Proceedings of ACM SIGMETRICS, Saint-Malo, France, ACM Press, Jun. 26-30, 2006. 335-346
[39] X. Zhang, J. Liu, B. Li, et al. CoolStreaming/DONet: A Data-Driven Overlay Network for Efficient Live Media Streaming. in: Proceedings of the IEEE Computer and Communications Societies (INFOCOM), Miami, USA. IEEE Press, Mar. 13-17, 2005.2102-2111
[40] P. Dhungel, X. Hei, K. W. Ross, et al. The Pollution Attack in P2P Live Video Streaming: Measurement Results and Defenses. in: Proceedings of ACM SIGCOMM Workshop on Peer-to-Peer Streaming and IPTV (P2P-TV), Kyoto, Japan, ACM Press, Aug. 31,2007. 323-328
[41] F. Benevenuto, M. Vasconcelos, J. Almeida, et al. Impact of Peer Incentives on the Dissemination of Polluted Content. in: Proceedings of ACM Symposium on Applied Computing (SAC), Dijon, France, ACM Press, Apr. 23-27,2006. 1875-1879
[42] A. J. Ganesh, A.M. Kermarrec, L. Massoulie. Peer-to-peer Membership Management for Gossip-based Protocols. in: Transactions on Computers, Feb. 2003, 52(2): 139-149
[43] J. Liang, N. Naoumov, K. W. Ross. Efficient Blacklisting and Pollution-level Estimation in P2P File-sharing Systems. in: Proceedings of the Asian Internet Engineering Conference (AINTEC), Bangkok, Thailand, Dec. 13-15,2005
[44] C. K. Wong, S. S. Lam. Digital Signatures for Flows and Multicasts. in: IEEE/ACM Transactions on Networking, Aug. 1999,7(4): 502-513
[45] E. Palomar, J. M. Estevez-Tapiador, J. C. Hernandez-Castro, et al. A Protocol for Secure Content Distribution in Pure P2P Networks. in: Proceedings of the 17~(th) International Conference on Database and Expert Systems Applications (DEXA'06), Krakow, Poland, Sep. 4-8,2006. 712-716
[46] J. Scott. Social Network Analysis: A Handbook. Sage, London, 2nd edition, 2000
[47] H. Ebel, J. Davidsen, S. Bornholdt. Dynamics of Social Networks. in: Complexity, 2002, 8(2):24-27
[48] R. Pastor-Satorras, A. Vespignani. Epidemic Spreading in Scale-Free Networks. in: Physical Review Letters, 2001, 86(14):3200
[49] Rose 病毒解决办灶,http://baike.baidu.com/view/869091.htm
[50] Nimaya Worm, http://it.rising.com.cn/Channels/Service/2006-11/1163505486d3873 4.shtml.
[51] N. Weaver, S. Staniford, V. Paxson. Very Fast Containment of Scanning Worms. in: Proceedings of the 12~(th) USENIX Security Symposium (Security'04), Aug. 9-13, 2004
[52] A. Levi, C. K. Koc. Risks in Email Security. in: Communications of the ACM, , August 2001,44(8): 112-112
[53] K. Takahashi, T. Abe, M. Kawashima. Stopping Junk Email by Using Conditional ID Technology: privango. in: NTT Technical Review, 2005, 3(3):52-56
[54] T. Oda, T. White. Immunity from Spam: an Analysis of an Artificial Immune System for Junk Email Detection. in: Proceedings of the 4~(th) International Conference on Artificial Immune Systems, Banff, Alberta, Canada, Springer, Aug. 14-17, 2005. 276-289
[55] Symantec Security Products, http://www.symantec.com
[56] P. Holme. Efficient Local Strategies for Vaccination and Network Attack. in: Europhys. Lett. 2004, 68:908-914
[57] F. Castaneda, E. C. Sezer and J. Xu. WORM vs. WORM: Preliminary Study of an Active Counter-attack Mechanism. in: Proceedings of ACM Workshop on Rapid Malcode (WORM), Fairfax, USA, ACM Press, Oct. 2004. 83-93
[58] D. Moore, C. Shannon, G. M. Voelker, et al. Internet Quarantine: Requirements for Containing Self-propagating Code. in: Proceedings of the 22~(nd) Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'03), San Francisco, USA, Mar. 2003. 1901-1910
[59] K. G. Anagnostakis, M. B. Greenwald, S. Ioannidis, et al. A Cooperative Immunization System for an Untrusting Internet. in: Proceedings of the 11~(th) IEEE International Conference on Networking (ICON'03), Sydney, Australia IEEE Press, Sep. 28-Oct. 1,2003.403-408
[60] O. Diekmann, J. A. P. Heesterbeek. Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. New York: Wiley, 2000
[61] C. Wong, C. Wang, D. Song, et al. Dynamic Quarantine of Internet Worms. in: Proceedings of the IEEE International Conference on Dependable Systems and Networks (DSN), Palazzo dei Congressi, Florence, Italy, Jun. 28-Jul. 1,2004. 73-82
[62] L. Chen, K. M. Carley. The Impact of Countermeasure Propagation on the Prevalence of Computer Viruses. in: IEEE Transactions on Systems, Man, and Cybernetics,Part B:Cybernetics,Apr.2004,34(2):823-833
[63]Z.Dezso,A.-L.Barabsi.Halting Viruses in Scale-Free Networks.in:Physical Review E,2002,65:055103
[64]R.P.Satorras,A.Vespignani.Immunization of Complex Networks.in:Physical Review E,2002,65:036104
[65]R.Pastor Satorras and A.Vespignani.Epidemics and Immunization in Scale-Free Networks.in:Handbook of Graphs and Networks:From the Genome to the Internet,Wiley-VCH,2003
[66]R.Cohen,S.Havlin,D.Ben-Avraham.Efficient Immunization Strategies for Computer Networks and Populations.in:Physical Review Letters,2003,91(24),247901
[67]金海,廖小飞.P2P技术原理与应用.中兴通讯技术,2007,13(6):1-5
[68]X.Huang,Y.Li,R.Yang,et al.Enhancing Attack Survivability of Gnutella-like P2P Networks by Targeted Immunization Scheme.in:Proceedings of the 6~(th) International Conference on Parallel and Distributed Computing,Applications and Technologies (PDCAT'05),Dalian,China,IEEE Press,Dec.5-8,2005.503-506
[69]M.M.Williamson.Throttling Viruses:Restricting Propagation to Defeat Mobile Malicious Code.in:Proceedings of ACSAC'02,Las Vegas,USA,IEEE Press,Dec.9-13,2002.61-68
[70]A.Ganesh,D.Gunawardena,P.Key,et al.Efficient Quarantining of Scanning Worms:Optimal Detection and Coordination.in:Proceedings of the 25~(th) Annual Joint Conference of the 25~(th) Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM),Barcelona,Spain,IEEE Press,April 2006.1-13
[71]L.Xie and S.Zhu.A Feasibility Study on Defending against Ultra-fast Topological Worms.in:Proceedings of the 7~(th) International Conference on Peer-to-Peer Computing(P2P'07),Galway,Ireland,IEEE Press,Sep.2-5,2007.61-70
[72]F.Freitas,R.Rodrigues,C.Ribeiro,et al.Verme:Worm Containment in Peer-to-Peer Overlays.in:Proceedings of the 6th International Workshop on Peer-to-Peer Systems(IPTPS'07),Bellevue,WA,USA,Feb.26-27,2007
[73]S.Yang,H.Jin,B.Li,et al.The Content Pollution in Peer-to-Peer Live Streaming Systems:Analysis and Implications.in:Proceedings of the 37th International Conference on Parallel Processing(ICPP),Portland,Oregon,USA.IEEE Press,Sep.8-12,2008.652-659
[74] S. Yang, H. Jin, B. Li, et al. A Modeling Framework of Content Pollution in Peer-to-Peer Video Streaming Systems. in: Computer Networks, Elsevier, 2009, doi:10.1016/j.comnet.2009.06.004
[75] N. Christin, A. S. Weigend, J. Chuang. Content Availability, Pollution and Poisoning in File Sharing Peer-to-Peer Networks. in: Proceedings of the 6~(th) ACM Conference on Electronic Commerce (EC'05), Vancouver, British Columbia, Canada, ACM Press, Jun. 2005. 68-77
[76] B. Li, S.-S. Xie, G. Y. Keung, et al. Inside the New Coolstreaming: Principles and Measurements. in: IEEE Journal on Selected Areas in Communications, Special Issue on Advances in Peer-to-Peer Streaming System, Dec. 2007,25(9): 1-13
[77] C. Zhang, H. Jin, D. Deng, et al. Anysee: Multicast-based Peer-to-Peer Media Streaming Service System. in: Proceedings of Asia-Pacific Conference on Communications (APCC), Perth, Australia, Oct. 3-5,2005. 274-278
[78] S. Yang, H. Jin, X, Tu. TOBAB: A Trend-Oriented Bandwidth Adaptive Buffering in Peer-to-Peer Streaming System. in: Proceedings of the 3~(rd) International Conference on Autonomic and Trusted Computing (ATC'06), Wuhan and Three Gorges, China, Springer, Sep. 3-6,2006. 113-122
[79] M. Garetto, D. R. Figueiredo, R. Gaeta, et al. A Modeling Framework to Understand the Tussle between ISPs and Peer-to-Peer File Sharing Users. in: Performance Evaluation, Springer, Oct. 2007, 64(9-12):819-837
[80] Y.-H. Chu, S. G. Rao and H. Zhang. A Case for End System Multicast. in: Proceedings of International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), Santa Clara, CA, ACM Press, Jun. 18-21, 2000. 1-12
[81] D. Tran, K. Hua and T. Do. ZIGZAG: An Efficient Peer-to-Peer Scheme for Media Streaming. in: Proceedings of the 22~(nd) Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'03), San Francisco, USA, IEEE Press, Mar. 30-Apr. 3,2003. 1283-1292
[82] PeerCast P2P Radio, http://www.peercast.org
[83] F. Wang, Y. Xiong, J. Liu. mTreebone: A Hybrid Tree/Mesh Overlay for Application-Layer Live Video Multicast. in: Proceedings of the 27~(th) International Conference on Distributed Computing Systems (ICDCS'07), Lisboa, Portugal, IEEE Press, Jun. 25-27,2006.49-49
[84] F. Wang, J. Liu, Y. Xiong. Stable Peers: Existence, Importance, and Application in Peer-to-Peer Live Video Streaming.in:Proceedings of the 26~(th) Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM),Phoenix,AL,USA.IEEE Press,Apr.13-18,2008.1364-1372
[85]Q.Huang,H.Jin,X.Liao.P2P Live Streaming with Tree-Mesh Hybrid Overlay.in:Proceedings of the 37~(th) International Conference on Parallel Processing(ICPP'07)Workshop on HOT-MP2P,Xi'an,China,IEEE Press,Sep.10-14,2007.55-55
[86]S.Saroiu,K.P.Gummadi,S.D.Gribble.Measuring and Analyzing the Characteristics of Napster and Gnutella Hosts.in:Multimedia System,Aug.2003,9(2):170-184
[87]S.Yang,H.Jin,B.Li,et al.Measuring Web Feature Impacts in BitTorrent-like Systems.in:Proceedings of The Fifth International ICST Conference on Heterogeneous Networking for Quality,Reliability,Security and Robustness (QShine'08),Hong Kong,China,Jul.28-31,2008
[88]S.Yang,H.Jin,B.Li,et al.Measuring Web Feature Impacts in Peer-to-Peer File Sharing Systems.in:Computer Communications,Elsevier,2009,doi:10.1016/j.comcom.2009.02.011
[89]B.Cohen.Incentives Build Robustness in BitTorrent.in:Proceedings of P2P Economics Workshop'03,Berkeley,USA,Jun.2003
[90]S.Yang,H.Jin,X.Liao,et al.Modeling Modern Social-Network-Based Epidemics:A Case Study of Rose.in:Proceedings of the 5~(th) International Conference on Autonomic and Trusted Computing(ATC'08),Oslo,Norway,Springer,Jun.23-25,2008.302-315
[91]A.Grabowskia,R.A.Kosifiski.The SIS Model of Epidemic Spreading in a Hierarchical Social Network.in:Acta.Phys.Polon.B,2005,36:1579-1593
[92]Z.Liu and B.Hu.Epidemic Spreading in Community Networks.in:Europhysics Letters,2005,72(2):315
[93]R.Pearlman.An Overview of PKI Trust Models.in:IEEE Network,1999,13(6):38-43
[94]S.Yang,H.Jin,B.Li,et al.Worm Containment in Peer-to-Peer Networks.in:Proceedings of International Conference on Scalable Computing and Communications(ScalCom),Dalian,China,IEEE Press,Sep.25-27,2009.to appear
[95]韩宗芬,陶智飞,杨思睿,等.一种基于自治域的协同入侵检测与防御机制.华 中科技大学学报(自然科学版),2006,34(12):53-55
[96]D.Moore,C.Shannon.Code-Red:a Case Study on the Spread and Victims of an Internet Worm.in:Proceedings of the 2~(nd) ACM SIGCOMM Workshop on Internet Measurement(IMW'02),Marseille,France,ACM Press,Nov.6-8,2002.273-284
[97]D.Moore,V.Paxson,S.Savage,et al.Inside the Slammer Worm.in:IEEE Security and Privacy Magazine,Jul.2003,1(4):33-39
[98]M.Crotti,M.Dusi,F.Gringoli,et al.Traffic Classification through Simple Statistical Fingerprinting.in:ACM SIGCOMM Computer Communication Review,,Jan.2007,37(1):7-16
[99]S.Yang,H.Jin,X.Liao,et al.OnRipple:A Distributed Overlay Framework for Targeted Immunization in Large-Scale Networks.in:Proceedings of the 8~(th) ACIS International Conference on Software Engineering,Artificial Intelligence,Networking and Parallel/Distributed Computing(SNPD'07),Qingdao,China,IEEE Press,Jul.30-Aug.1,2007.911-916
[100]M.E.J.Newman.The Structure and Function of Complex Networks.in:SIAM Review,2003,45(2):167-256
[101]A.Montresor,M.Jelasity,O.Babaoglu.Robust Aggregation Protocols for Large-Scale Overlay Networks.in:Technical Report,University of Bologna,Italy,Dec.2003,UBLCS-2003-16
[102]W.Aiello,F.Chung,L.Lu.A Random Graph Model for Massive Graphs.in:Proceedings of the 32~(nd) Annual ACM Symposium on Theory of Computing,Association of Computing Machinery,New York,USA,ACM Press,2000.171-180
[103]B.Wong,A.Slivkins,E.G.Sirer.Meridian:A Lightweight Network Location Service without Virtual Coordinates.in:Proceedings of ACM SIGCOMM,Philadelphia,USA,ACM Press,Aug.22-26,2005.85-96